bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrospective analysis of pre‐ and peri‐operative imaging in confirmed proximal colonic cancers – possible implications for screening flexible sigmoidoscopy
Authors: Peravali R. , Kandiah K. , Surah A. , Murria P. , Taniere P. , Radley S.
Published: May 2008

Objective  Faecal occult blood testing is being introduced for population screening in the United Kingdom. Flexible sigmoidoscopy may provide a viable alternative. The outcomes of the flexible sigmoidoscopy trial are awaited but the most obvious disadvantage is that only the lower third of the colon is examined and proximal pathology cannot be excluded. The relationship between proximal pathology and distal findings at flexible sigmoidoscopy is uncertain. The aim of this study was to determine the incidence of distal neoplasia in patients with confirmed proximal cancers of the colon.

Method  All confirmed proximal colonic cancers (defined as those proximal to the splenic flexure) were identified from a database of pathology specimens at a single centre between January 1999 and August 2006. A retrospective analysis of preoperative and peri‐operative mucosal imaging (contrast enema, colonoscopy and CT colonography) was conducted to identify any distal neoplasia in these patients.

Results  A total of 348 patients were identified. Pre‐ or peri‐operative mucosal imaging was identified in 231 (66%) and 49 (21%) had distal neoplasia. Nineteen (8%) of these patients would have gone on to have a colonoscopy based on the UK flexible sigmoidoscopy trial protocol and 92% of the cohort would not have had a colonoscopy.

Conclusion  Nearly 80% of confirmed proximal cancers in our series did not have any demonstrable distal neoplasia. Only 8% of our cohort would have proceeded to colonoscopy. A very significant number of proximal cancers would not have been detected.
Results of the United Kingdoms first pilot study for nonmedical endoscopy practitioners
Authors: Gardiner A. B.
Published: May 2008

Objective  Spencer and Ready published the first description of nonmedically qualified endoscopists in 1977 [Dis Colon Rectum 1977; 20: 94]. Since then there has been an explosion of interest in this concept. Duthie et al. [Gut 1998; 43: 711] first described Nurse Endoscopy (NE) in the UK in 1998. In recent years, endoscopy services in England have been subject to review as a consequence of perceived inadequacies in service provision and delivery.

Method  Increasing pressure on endoscopic services led the Modernisation Agency to commission a pilot study evaluating nontraditional individuals to practice flexible sigmoidoscopy (FS). A science graduate, basic grade nurse and nonclinical member of staff were successfully trained. As a result, a second pilot scheme was introduced, whereby nine nonmedically qualified individuals received education and training in FS. A curriculum was designed, developed and implemented to create an endoscopic practitioner (EP) who was both safe and competent to undertake FS. The student backgrounds included administration, health‐care assistants, phlebotomist, junior doctor assistant and clinical physiologist.

Results  In the context of academic achievement, prescribed learning outcomes were achieved at a rate of 93% (101 from 108) of success in first attempt at assessment. In terms of practical achievement, each student demonstrated competency in FS.

Conclusion  The curriculum designed provides a suitable framework to develop individuals with the necessary knowledge, skills and attitudes required for safe, competent practice within FS. This indicates that the curriculum provides a broad range of learning, teaching and assessment strategies befitting to a range of individuals.
Familial colorectal cancer: a concept revisited
Authors: Martellucci J. , Civitelli S. , Dhamo A. , Tanzini G.
Published: May 2008

Objective  The family history of patients with colorectal cancer (CRC) shows an increased risk of disease although evident inherited syndromes are demonstrable in only a small percentage of patients. The purpose of this study was to identify factors that might suggest an inherited component in the transmission of CRC.

Method  The study monitored 880 consecutive patients between 1980 and 2005 treated for CRC.

Results  Familial adenomatous polyposis (FAP) was found in only one patient, and a classical mutation of hereditary nonpolyposis colon cancer was found in only two patients. The risk assessment was possible mainly because of factors such as early onset CRC, the presence of multiple primary tumours and a high risk family history. Considering these 36 more patients were suspected to be high risk and referred for further genetic testing. At least one first‐degree relative with CRC was reported in 140 patients. In 49 patients, CRC was diagnosed before 50 years of age. Multiple primary tumours, colonic or extra colonic, synchronous or metachronous were found in 136 patients.

Conclusion  Our study suggests that if only patients with identified mutations are taken into consideration, then the percentage of evident hereditary colon cancer is very low, but this percentage quickly increases if we make marginal adjustments to the identifying criteria. It seems that it is the physician’s clinical suspicion, more than the fulfilment of rigid criteria, which plays a fundamental role in the timely identification and a subsequent focused treatment of patients with hereditary CRC.
The effect of 4% icodextrin solution on adhesiolysis surgery time at the Hartmann’s reversal: a pilot, multicentre, randomized control trial vs lactated Ringer’s solution
Authors: Kössi J. , Grönlund S. , Uotila‐Nieminen M. , Crowe A. , Knight A. , Keränen U.
Published: May 2008

Objective  A pilot randomized controlled clinical multicentre trail was established to compare intraperitoneal 4% icodextrin (ID) solution with lactated Ringer’s solution (LRS) on adhesion formation after Hartmann’s procedure. The adhesiolysis surgery time during Hartman’s reversal was used as a marker of the severity of adhesions.

Method  Patients scheduled for Hartmann’s resection were randomized at surgery to either of the two study solutions used as an irrigant during the operation and instilled (1000 ml) at the end of surgery. During the reversal procedure, the time for small bowel adhesiolysis was recorded.

Results  On completion of 17 eligible patients, an interim analysis was performed. There were no complications following the use of 4% ID solution. The mean (SD) total adhesiolysis times in patients treated with 4% ID solution and LRS were 30.8 (18.0) min and 47.6 (45.7) min, respectively. The mean reduction of 16.8 min, although greater than expected, was not statistically significant (P = 0.33) because of the large variance in adhesiolysis times. Further statistical analysis showed that to achieve significance for the observed differences and variance, a minimum of 240 patients in each group would be required.

Conclusion  Icodextrin treatment resulted in a decreasing trend in adhesiolysis time. The use of 4% ID solution in peritonitis patients seemed to be safe. Because of larger than expected variations in adhesiolysis times, this pilot study was underpowered to meet the study end‐point and further statistical modelling estimated that significance cannot be reached within a reasonable time scale. Other models should be used to evaluate the efficacy of anti‐adhesive agents.
Rhomboid excision and Limberg flap for managing pilonidal sinus: long‐term results in 411 patients
Authors: Akin M. , Gokbayir H. , Kilic K. , Topgul K. , Ozdemir E. , Ferahkose Z.
Published: May 2008

Objective  To investigate the results of rhomboid excision and the Limberg flap procedure to treat pilonidal sinus disease.

Method  The records of 411 patients with pilonidal sinus disease, who underwent rhomboid excision and Limberg flap procedure, were analysed. All sinus tracks were resected en bloc, and a Limberg flap was prepared from left or right gluteal region. A suction drain was routinely used.

Results  The mean follow‐up period was 109.2 ± 4.5 months (range: 12–183 months). Recurrence occurred in 12 (2.91%) patients who were all male. In 42 (10.21%) patients, anaesthesia or hypoaesthesia of the upper portion of the flap occurred; this was temporary in 25 patients. Twelve (2.91%) patients developed a seroma and 15 (3.64%) a wound infection. The average hospital stay was 3.2 days (range: 1–10 days), and the average time of return to work was 12.4 days (range: 7–18 days). The average time to walk without pain was 13.4 days (range: 10–28 days) and the average time to sitting on the toilet without pain was 16.1 days (range: 12–28 days).

Conclusion  The Limberg flap procedure is effective and has a low complication rate, short time for returning to normal activity and short hospitalization.
Effectiveness and Efficiency of Cross‐Border Knowledge Transfer: An Empirical Examination
Authors: Pérez‐Nordtvedt Liliana , Kedia Ben L. , Datta Deepak K. , Rasheed Abdul A.
Published: May 2008

abstract  Based on a sample of 102 US organizations, this study examines the impact of knowledge characteristics, recipient learning intent, source attractiveness, and relationship quality on the effectiveness and efficiency of knowledge transfer from the international business affiliates of these organizations. Findings indicate that recipient learning intent and source attractiveness positively impact the effectiveness of knowledge transfer. In addition, recipient learning intent was found to have a positive effect on knowledge transfer efficiency. In particular, results highlight the strong positive impact that the quality of the relationship between the source and the recipient has on both the efficiency and effectiveness of cross‐border knowledge transfer. The study also indicates that knowledge value is positively associated with recipient learning intent and that knowledge value, rarity and non‐substitutability influence source attractiveness. Finally, findings suggest that the relationship between knowledge characteristics and knowledge transfer is partially mediated by recipient learning intent and source attractiveness.
Transformation Networks in Innovation Alliances – The Development of Volvo C70
Authors: Harryson Sigvald J. , Dudkowski Rafal , Stern Alexander
Published: May 2008

abstract This paper addresses an important gap in the literature intersection between network theory and networked innovation by developing a theoretical framework on how to leverage learning alliances across extra‐ and intra‐corporate levels to support both exploration and exploitation of innovation to secure its creationandits implementation. A detailed case of the Volvo C70 development is analysed with focus on how the full innovation from exploration to exploitation of innovation seem to rely on fundamentally different types and structures of networks. Our detailed description and analysis of how a ‘transformation network’ was established and operated across different organizational levels to secure not only transfer, but also transformation and integration of knowledge into commercialized innovation makes an important contribution to extant theory on inter‐organizational knowledge transfer and networking.
PERFORMANCE ANALYSIS FOR A SAMPLE OF MICROFINANCE INSTITUTIONS IN INDIA
Authors: De CROMBRUGGHE Alain , TENIKUE Michel , SUREDA Julie
Published: May 2008

ABSTRACT**:  We use regression analysis to study the determinants of self‐sustainability of a sample of microfinance institutions in India. These institutions stand out by their ability and willingness to report financial and operational data to Sa Dhan, a know‐how sharing organization. We investigate particularly three aspects of sustainability: cost coverage by revenue, repayment of loans and cost‐control. Our results suggest that the challenge of covering costs on small and partly unsecured loans can indeed be met, without necessarily increasing the size of the loans or raising the monitoring cost. The analysis suggests other ways to improve the financial results, like a better targeting of the interest rate policy or increasing the number of borrowers per field officer especially in collective delivery models.
Semantic Interoperability through the Definition of Conceptual Model Transformations
Authors: Staub Peter , Gnägi Hans Rudolf , Morf Andreas
Published: May 2008

The integration of distributed geospatial data is a great issue in GI Science. Hereby, the collection of data from different systems and different structures as well as across country borders is a problem. We explain a model‐based four‐step approach to conceptual data modelling. Within this approach, we introduce a methodology to map data models on the conceptual level without touching data formats. First, we developed a conceptual mapping language called “UMLT” which is the core of our approach. Furthermore, we integrated UMLT into the Model‐Driven Architecture where a conceptual model mapping is referred to as a platform independent model mapping. Finally, the data format transformation is deduced from the model mapping automatically. This represents the implementation mapping from a platform independent model to a platform specific model. Together with transformation operations for attribute mapping, this approach is a means for effective and enhanced semantic interoperability.
A GIS‐Based Tool for Spatial and Distributed Hydrological Modelling: CLASS Spatial Analyst
Authors: Teng Jin , Vaze Jai , Tuteja Narendra K , Gallant John C
Published: May 2008

CLASS Spatial Analyst is a GIS tool which can be used to support spatially distributed hydrological modelling. The tool generates a number of spatial layers that can be used for many practical applications. These include climate zoning, multi‐resolution DEMs, Compound Topographic Index (CTI) (also referred to as Topographic Wetness Index, TWI), lateral multiple flow paths, accumulation and dispersion of water and solutes from hazard areas, estimation of soil depth, soil material/horizon distribution and soil moisture storage capacity in different parts of the landscape. Although each of these tasks can be undertaken separately using spatial software packages such as ArcGIS, GRASS, TIME, and MapInfo, this tool puts together all these tasks into a single application which provides the user with an option of undertaking some or all of them within this application. The technology used in this tool is supported by various peer‐reviewed publications (e.g. Tarboton 1997, Gallant and Dowling 2003).
A GIS‐Based Model to Determine Site Suitability of Emergency Evacuation Shelters
Authors: Kar Bandana , Hodgson Michael E
Published: May 2008

In recent years, the increase in the number of hurricanes and other costal hazards in the US pose a tremendous threat to the residents of coastal states. According to the National Hurricane Center, Florida is the most vulnerable coastal state to hurricanes. Mitigation policies have been formulated to reduce mortality and provide emergency services by evacuating people from the hazard zone. Many of these evacuees, particularly the elderly or lower income populations, rely on evacuation shelters for temporary housing. Because of the cost and limited use, evacuation shelters are almost exclusively dual use shelters where the primary purpose of the facility is for some other public function (e.g. school, hospital, etc.). In 2000, the estimated shortage of public shelter spaces in Florida was about 1.5 million. The purpose of this study was to rank the existing and candidate shelters (schools, colleges, churches and community centers) available in the state based on their site suitability. The research questions examined in this study include: (1) How many candidate shelters are located in physically suitable areas (e.g. not in a flood prone area, not near hazardous facilities, etc.)?; (2) How many existing shelters are located in physically unsuitable areas, but in socially suitable areas (situated in areas with demand)?; (3) How many alternative existing and/or candidate shelters with high/very high physical suitability are located near physically unsuitable existing shelters and thus, may be better choices for a shelter?; and (4) How many existing shelters located in physically unsuitable areas are not near alternative existing and/or candidate shelters? A Geographic Information System‐based suitability model integrating Weighted Linear Combination (WLC) with a Pass/Fail screening technique was implemented for the 17 counties of Southern Florida. It was found that 48% of the existing shelters are located in physically unsuitable areas. Out of all the candidate shelters, 57% are located in physically unsuitable areas. For 15 of the existing shelters in unsuitable locations, no alternative candidate or existing shelter with medium to high physical suitability exists within 10 miles (16.1 km).
Using Topological Relationships to Inform a Data Integration Process
Authors: Hope Sue , Kealy Allison
Published: May 2008

When spatial datasets are overlaid, corresponding features do not always coincide. This may be a result of the datasets having differing quality characteristics, being captured at different scales or perhaps being in different projections or datums. Data integration methods have been developed to bring such datasets into alignment. Although these methods attempt to maintain topological relationships within each dataset, spatial relationships between features in different datasets are generally not considered. The preservation of inter‐dataset topology is a research area of considerable current interest. This research addresses the preservation of topology within a data integration process. It describes the functional models established to represent a number of spatial relationships as observation equations. These are used to provide additional information concerning the relative positions of features. Since many topological relationships are best modelled as inequalities, an algorithm is developed to accommodate such relationships. The method, based on least squares with inequalities (LSI), is tested on simulated and real datasets. Results are presented to illustrate the optimal positioning solutions determined using all of the available information. In addition, updated quality parameters are provided at the level of the individual coordinate, enabling communication of local variation in the resultant quality of the integrated datasets.
The Development of the Chagas’ Online Data Entry System (CODES‐GIS)
Authors: Blackburn Jason K , Curtis Andrew , Mujica Frances Currin , Jones Farrell , Dorn Patricia , Coates Rosamond
Published: May 2008

This article describes a web‐based data entry and GIS‐driven mapping system designed for an ethnographic and entomological survey of Chagas’ disease, an emerging zoonotic disease, and Triatoma dimidiata, a primary vector, in the Los Tuxtlas region of Veracruz, Mexico. To better understand this disease in the region, a collaborative, multi‐disciplinary study was initiated to conduct a spatial investigation of T. dimidiata and a community‐by‐community survey of local perceptions of the disease. In order to facilitate such a collaborative effort the CODES‐GIS was developed. This system allows for (near) real‐time mapping, analyses, disease reporting, and results sharing. CODES‐GIS provides a framework for a research team working in a remote area with limited technology, software, or GIS expertise to benefit from (near) real‐time spatial analyses performed at collaborating institutions. The system is bi‐directional, where field personnel can upload data to the system for field‐based map production. Likewise, laboratory personnel can upload diagnostics data for viewing by field personnel. In this way, the system provides a virtual link between the field and the laboratory to increase the speed at which results are returned to the local community. The CODES‐GIS is described along with a selection of study results.
A NOTE ON RELATIONS BETWEEN SEASONALLY ADJUSTED VARIABLES
Authors: Newbold Paul
Published: May 2008

Abstract. This paper examines, with reference to some well known data, possible difficulties in the fitting of simple non‐seasonal models to seasonally adjusted time series data.
THE ESTIMATION OF RANDOM COEFFICIENT AUTOREGRESSIVE MODELS. I
Authors: Nicholls D. F. , Quinn B. G.
Published: May 2008

Abstract. This paper is concerned with autoregressive models in which the coefficients are assumed to be not constant but subject to random perturbations so that we are considering a class of random coefficient autoregressive models. By means of a two stage regression procedure estimates of the unknown parameters of these models are obtained. The estimates are shown to be strongly consistent and to satisfy a central limit theorem. A number of Monte Carlo experiments was carried out to illustrate the estimation procedure and their results are reported.
STATE‐DEPENDENT MODELS: A GENERAL APPROACH TO NON‐LINEAR TIME SERIES ANALYSIS
Authors: Priestley M. B.
Published: May 2008

Abstract.We construct a general class of non‐linear models, called ‘state‐dependent models’, which have a very flexible non‐linear structure and which contain, as special cases, bilinear, threshold autoregressive, and exponential autoregressive models. We describe a sequential type of recursive algorithm for identifying state‐dependent models, and show how such models may be used for forecasting and for indicating specific types of non‐linear behaviour.
THE DISTRIBUTION OF PERIODOGRAM ORDINATES
Authors: Zhao‐Guo Chen , Hannan E. J.
Published: May 2008

Abstract. The empirical distribution function of yi=I(ωj)/{2πf(ωj)}, ωj= 2πj/T, where I(ω) is the periodogram for a set of observations from a stationary time series with spectral density f(ω), is shown to converge, almost surely, to the distribution with density exp(‐ x), under appropriate conditions. The same methods are used to prove the convergence, almost surely, of an estimate of the prediction error variance constructed from the I(ωj) and of the complex empirical distribution function based on the Fourier coefficients.
AUTOREGRESSIVE MOVING AVERAGE PROCESSES WITH NON‐NORMAL RESIDUALS
Authors: Davies Neville , Spedding Trevor , Watson William
Published: May 2008

Abstract. ARMA processes with non‐normal residuals have applications in surface metrology and have recently been shown by Nelson and Granger (1979) to occur in modelling economic time series. In this paper we obtain the theoretical relationship between the skewness and kurtosis of an ARMA process and the corresponding parameters of its generating noise series and consider some of the implications of these results. Simulation methods for any ARMA process with given skewness and kurtosis, using Johnson transformations are briefly discussed.
A TIME‐SERIES TEST OF THE NATURAL‐RATE HYPOTHESIS
Authors: Evans Paul
Published: May 2008

Abstract. This paper develops a test of the natural‐rate hypothesis that does not require strong assumptions about the structure of the economy or how the public anticipates inflation. The paper then applies this test to U.S. data, finding that one cannot reject the natural‐rate hypothesis.
NECESSARY AND SUFFICIENT CONDITIONS FOR CAUSALITY TESTING IN MULTIVARIATE ARMA MODELS
Authors: Kang Heejoon
Published: May 2008

Abstract.The necessary and sufficient conditions for Granger causality are provided. The condition is that some linear combinations of certain elements of AR matrix and certain elements of MA matrix must vanish. It is less restrictive than the condition heretofore utilized in the literature which is only sufficient in which certain elements in AR matrix as well as certain elements in MA matrix themselves are zero. A proper parsimonious parametric test procedure is also established by using the necessary and sufficient condition.
A NONSTATIONARY TIME SERIES MODEL AND ITS FITTING BY A RECURSIVE FILTER
Authors: Kitagawa Genshiro
Published: May 2008

Abstract. The use of the state space representation for the analysis of nonstationary time series is proposed. For the fitting of the models, the use of a modified AIC based on the likelihood of the innovation process is proposed. A square root filter/smoother algorithm for the evaluation of the likelihood and state estimation is discussed.
RANK TESTS FOR SERIAL DEPENDENCE
Authors: Dufour Jean‐Marie
Published: May 2008

Abstract.A family of linear rank statistics is proposed in order to test the independence of a time series, under the assumption that the random variables involved have symmetric distributions with zero medians, without the standard assumptions of normality or identical distributions. The family considered includes analogues of the sign. Wilcoxon signed‐rank and van der Waerden tests for symmetry about zero and tables constructed for these tests remain applicable in the present context. The tests proposed are exact and may be applied to assess serial dependence at lag one or greater. The procedures developed are illustrated by a test of the efficiency of forward exhange rates as predictors of future spot rates during the German hyperinflation.
THE ESTIMATION AND PREDICTION OF SUBSET BILINEAR TIME SERIES MODELS WITH APPLICATIONS
Authors: Gabr M. M. , Rao T. Subba
Published: May 2008

Abstract.In this paper we define subset bilinear time series models, and then describe an algorithm for the estimation of these models. It is also pointed out that for this class of non‐linear time series models, it is possible to obtain optimal several step predictors. The estimation technique of these models is illustrated with respect to three time series, and the optimal several steps ahead forecasts of these time series models are calculated. A comparison of these forecasts is made with the forecasts obtained by the best linear autoregressive and threshold autoregressive models. The residuals obtained from the models are tested for independence and Gaussianity using higher order moments.
THE ESTIMATION OF RANDOM COEFFICIENT AUTOGRESSIVE MODELS. II
Authors: Quinn B. G. , Nicholls D. F.
Published: May 2008

Abstract. In Nicholls and Quinn (1980) a procedure was proposed for the determination of strongly consistent estimates of random coefficient autoregressive models. These estimates are used here as starting values in a Newton‐Raphson algorithm which is employed to obtain the maximum likelihood estimates of a class of random coefficient autoregressions. The maximum likelihood estimates are shown to be strongly consistent and to satisfy a central limit theorem. The problem of testing for the randomness of the coefficients is also briefly discussed. The results of a number of simulations are reported which illustrate the theoretical results obtained.
FINITE SAMPLE PREDICTION AND OVERDIFFERENCING
Authors: Harvey A. C.
Published: May 2008

Abstract. If the process generating a time series contains a deterministic component the differencing operations carried out to achieve stationarity may lead to an ARMA model which is strictly noninvertible. This is known as overdifferencing but it is shown here that overdifferencing need not have serious implications for prediction provided that a finite sample prediction procedure is used. The proposed method is based on the Kalman filter and it allows both the optimal predictors and their mean square errors to be computed.
A TIME SERIES APPLICATION OF THE USE OF MONTE CARLO METHODS TO COMPARE STATISTICAL TESTS
Authors: Poskitt D. S. , Tremayne A. R.
Published: May 2008

Abstract.In this paper, we investigate the use of asymptotic theory to design and control simulation experiments concerning the finite sample properties of test statistics. The tests considered in the Monte Carlo experiments are various diagnostic checks which have been proposed for assessing the adequacy of the specification of open‐loop transfer function models. Attention is focussed on both the empirical size and power of the testing procedures examined and a simple descriptive measure of the relative performance of alternative tests based on changes in power resulting from variations in significance level is suggested. Whilst asymptotic theoretic considerations determine the parameter values selected, it is seen that useful information as to the actual small sample behaviour of the tests can be obtained by employing a direct modification to the standard theory.
THE STATISTICAL ANALYSIS OF PERTURBED LIMIT CYCLE PROCESSES USING NONLINEAR TIME SERIES MODELS
Authors: Ozaki T.
Published: May 2008

Abstract.Statistical analysis of perturbed limit cycle process is discussed. Limit cycles of van der Pol equation type are considered and statistical time series models for the perturbed limit cycle processes are presented. It is shown that the model shares some interesting qualitative properties although the presented models are different, in appearance, from the van der Pol equation. Applications of the model to the statistical analysis of Canadian Lynx data are also discussed with numerical results.
THE MARKET MODEL, CAPM AND EFFICIENCY IN THE FREQUENCY DOMAIN
Authors: Praetz Peter
Published: May 2008

Abstract. This paper develops a frequency domain capital asset pricing and market model as a generalization of the existing temporal theory using formal financial models which are functions of fewquency. The market model is tested empirically using monthly Melbourne Stock Exchange data from 1964–1976 and frequency domain testing of the CAPM is discussed with implications for stock market efficiency.
TESTING FOR THE RANDOMNESS OF AUTOREGRESSIVE COEFFICIENTS
Authors: Quinn B. G. , Nicholls D. F.
Published: May 2008

Abstract. Two tests are proposed for the hypothesis that data come from an autoregression against the hypothesis that they come from a random coefficient autoregression. The tests are derived from a consideration of the C(α) tests of Neyman, the analysis of tests based on the likelihood ratio being complicated by the fact that the vector of system parameters specified under the null hypothesis lies on the boundary of the parameter space. The asymptotic distributional properties are derived and the powers of the tests compared.
A NOTE ON USING THRESHOLD AUTOREGRESSIVE MODELS FOR MULTI‐STEP‐AHEAD PREDICTION OF CYCLICAL DATA
Authors: Tong H.
Published: May 2008

Abstract.We give a brief account of how the class of threshold autoregressive time series models may be used to make short, medium and long range predictions of cyclical data.
COMPARATIVE POWER STUDIES FOR GOODNESS OF FIT TESTS OF TIME SERIES MODELS
Authors: Clarke B. R. , Godolphin E. J.
Published: May 2008

Abstract.Power studies for three tests of fit, namely the classical test given by Whittle, the widely‐known test given by Ljung and Box, and the recent test given by Godolphin, are derived for the invertible time series models considered previously in an empirical study. The results demonstrate that it is possible to improve on the Ljung‐Box test by employing more empirically‐based alternatives. In particular, the test derived by Godolphin appears to be more powerful than the other tests. The results also suggest that the Whittle and Ljung‐Box tests are complementary, so that the combination of both may yield a sensitive test procedure.
SUFFICIENT STATISTICS FOR STATIONARY DISCRETE‐TIME GAUSSIAN RANDOM PROCESSES
Authors: Dickinson Bradley W.
Published: May 2008

Abstract. It is known that the distribution of N samples of a stationary Gaussian autoregressive process admits a sufficient statistic whose dimension is independent of N. We show that this property depends not on the absence of spectral zeros in autoregressive models, but rather on the fact that the class of models has a fixed set of spectral zeros.
TESTING FOR GAUSSIANITY AND LINEARITY OF A STATIONARY TIME SERIES
Authors: Hinich Melvin J.
Published: May 2008

Abstract. Stable autoregressive (AR) and autoregressive moving average (ARMA) processes belong to the class of stationary linear time series. A linear time series {} is Gaussian if the distribution of the independent innovations {ε(t)} is normal. Assuming that Eε(t) = 0, some of the third‐order cumulants cxxx=Ex(t)x(t+m)x(t+n) will be non‐zero if the ε(t) are not normal and Eε3(t)≠O. If the relationship between {x(t)} and {ε(t)} is non‐linear, then {x(t)} is non‐Gaussian even if the ε(t) are normal. This paper presents a simple estimator of the bispectrum, the Fourier transform of {cxxx(m, n)}. This sample bispectrum is used to construct a statistic to test whether the bispectrum of {x(t)} is non‐zero. A rejection of the null hypothesis implies a rejection of the hypothesis that {x(t)} is Gaussian. Another test statistic is presented for testing the hypothesis that {x(t)} is linear. The asymptotic properties of the sample bispectrum are incorporated in these test statistics. The tests are consistent as the sample size N→‐∞
Robust Hypothesis Testing and Robust Time Series Interpolation And Regression
Authors: Kassam Saleem A.
Published: May 2008

Abstract.Recent results on minimax robust time series interpolation and regression coefficient estimation are generalized and extended through a relationship with robust hypothesis testing. The spectral uncertainty classes in the time series problems are assumed to be convex and to satisfy an integral constraint such as on the variance of the process. It is shown that robust solutions in such cases can always be obtained from the least‐favourable probability density functions for corresponding hypothesis testing problems. A specific class, the bounded spectral densities from the band model, is considered to illustrate the results.
ON THE COVARIANCE OF THE PERIODOGRAM
Authors: Krogstad Harald E.
Published: May 2008

Abstract. The paper discusses the covariance of the periodogram from a zero mean fourth order stationary stochastic process. The fourth order cumulant term appearing in the covariance is shown to be a convolution between the fourth order cumulant spectrum and a bounded approximate identity, and this gives precise results about its asymptotic behaviour. The covariance is also studied both pointwise and as a measure of two variables. This leads to necessary and sufficient conditions for mean square consistency of estimates of the spectral moments and related parameters.
ON‐LINE VARIANCE ESTIMATION FOR THE STEADY STATE BAYESIAN FORECASTING MODEL
Authors: Cantarelis N. , Johnston F. R.
Published: May 2008

Abstract.The Bayesian approach to forecasting provides the user with distributional information which plays an important role in decision making. However, in practice, the process variances are unknown and therefore if the model operates with fixed estimates of these variances, the distributional information can be misleading. A method is proposed in this paper which produces on‐line maximum likelihood estimates of the variances for the steady state Dynamic Linear model, whose updating employs the Kalman filter. It makes use of a one‐dimensional class I multi‐process model approach which requires a set of initial values. In the limit the variance estimates are independent of the choice of initial values, but some practical suggestions are made which enable the procedure to converge faster. A numerical illustration and a number of points relevant to the performance of the model when tested under different choices of starting values are also given.
DIFFERENCING MULTIPLE TIME SERIES: ANOTHER LOOK AT CANADIAN MONEY AND INCOME DATA
Authors: Lütkepohl Helmut
Published: May 2008

Abstract.In multiple time series analysis it is sometimes suggested to remove non‐stationarities of the univariate subseries by differencing prior to the multivariate analysis. It is pointed out that, in general, this is not adequate if AR models are built even if stationarity of the univariate subseries can be induced by differencing. Canadian money and income data that were previously analysed by Hsiao are used to illustrate the resulting problems.
AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
Authors: Shumway R. H. , Stoffer D. S.
Published: May 2008

Abstract.An approach to smoothing and forecasting for time series with missing observations is proposed. For an underlying state‐space model, the EM algorithm is used in conjunction with the conventional Kalman smoothed estimators to derive a simple recursive procedure for estimating the parameters by maximum likelihood. An example is given which involves smoothing and forecasting an economic series using the maximum likelihood estimators for the parameters.
EMPIRICAL IDENTIFICATION OF MULTIPLE TIME SERIES
Authors: Tjøstheim Dag , Paulsen Jostein
Published: May 2008

Abstract.In the univariate case the problem of empirical identification consists in determining the order parametersp,dandqof ARIMA (p, d, q) processes. In this paper we introduce some new techniques for handling the corresponding problem for a multiple time seriesX(t) with the main emphasis on AR and MA models. Types of joint nonstationarity (or rather almost nonstationarity) are defined and a method of analyzing such structures based on the ordered eigenvalues of the functionC(t) =K(t)K‐1(0) is discussed, whereK(t) is the covariance function ofX(t). It is proposed that the further identification procedure should be based on twoX2statistics and on the estimated trace and eigenvalues ofC(t), the matrix correlation functionp(t) and the matrix partial correlation functionP(t). The suitability for identification purposes of each of these functions is examined in terms of such properties as scale‐invariance, existence of normalized eigenvalues and standard errors. The methods introduced are illustrated on a 5‐dimensional economic time series first studied by Quenouille and on a 4‐dimensional smulated MA series.
STATIONARY DISCRETE AUTOREGRESSIVE‐MOVING AVERAGE TIME SERIES GENERATED BY MIXTURES
Authors: Jacobs P. A. , Lewis P. A. W.
Published: May 2008

Abstract.Two simple stationary processes of discrete random variables with arbitrarily chosen first‐order marginal distributions, DARMA (p, N+ 1) and NDARMA (p, N), are given. The correlation structure of these processes mimics that of the usual linear ARMA (p, q) processes. The relationship of these processes to mover‐stayer models, and to models for discrete time series given separately by Lindqvist and Pegram is discussed.Ad hocnonparametric estimators for the parameters in the DARMA (p, N+ 1) and NDARMA (p, N) are given. A simulation study shows them to be as good as maximum likelihood estimators for the first‐order autoregressive case, and to be much simpler to compute than the maximum likelihood estimators.
ON THE ASYMPTOTIC EFFICIENCY OF ESTIMATORS OF THE PARAMETERS OF AN ARMA PROCESS
Authors: Kabaila Paul
Published: May 2008

Abstract. In this paper we derive a lower bound on the asymptotic covariance matrix of an estimator of the parameters of an autoregressive moving average (ARMA) process when the innovations are not necessarily Gaussian.
ASYMPTOTIC RELATIVE EFFICIENCY OF SOME TESTS OF FIT IN TIME SERIES MODELS
Authors: Saikkonen Pentti
Published: May 2008

Abstract.Two frequency domain tests of fit for autoregressive moving average time series models are considered. The tests are slight generalizations of those introduced by Cameron (1978) and Milhøj (1981). It is shown that according to asymptotic relative efficiency the test by Milhøj outperforms the test by Cameron. However, if asymptotic relative efficiency is used as a standard of comparison, both of these tests are extremely poor as compared to the well‐known time domain test of Box and Pierce (1970), for the asymptotic relative efficiency of the frequency domain tests as compared to the Box‐Pierce test is zero.
INVERSE AUTOCOVARIANCES AND A MEASURE OF LINEAR DETERMINISM FOR A STATIONARY PROCESS
Authors: Battaglia Francesco
Published: May 2008

Abstract. The inverse autocorrelations and autocovariances of a stationary stochastic process are generally used in the identification of ARMA models and linear systems, but they are also useful for studying linear relations inside the process as a whole.

Using inverse autocovariances, for any stationary process an ‘inverse process’ may be defined which may be considered a minimum variance linear filter, and turns out to be the best linear two‐sided interpolator for one unknown value.

Basing on these results an index of linear determinism is introduced to measure to what degree a stationary process satisfies a linear deterministic constraint. The behaviour of the index for ARMA processes is finally examined.
ESTIMATION OF THE ORDER OF A MOVING AVERAGE MODEL FROM AUTOREGRESSIVE AND WINDOW ESTIMATES OF THE INVERSE CORRELATION FUNCTION
Authors: Bhansali R. J.
Published: May 2008

Abstract.The autoregressive and window estimates of the inverse correlation function are used for estimating the order of a finite moving average process by using criteria similar to the FPEα criterion of Bhansali and Downham (1977). The asymptotic distribution of the estimates is derived. Their finite sample behaviour is examined by means of a simulation study.
NONPARAMETRIC ESTIMATORS FOR TIME SERIES
Authors: Robinson P. M.
Published: May 2008

Abstract.Kernel multivariate probability density and regression estimators are applied to a univariate strictly stationary time seriesXrWe consider estimators of the joint probability density ofXtat differentt‐values, of conditional probability densities, and of the conditional expectation of functionals ofXvgiven past behaviour. The methods seem of particular relevance in light of recent interest in non‐Gaussian time series models. Under a strong mixing condition multivariate central limit theorems for estimators at distinct points are established, the asymptotic distributions being of the same nature as those which would derive from independent multivariate observations.
ON THE DISTRIBUTION OF A SIMPLE STATIONARY BILINEAR PROCESS
Authors: Shou‐Ren Wang , Hong‐Zhi An , Tong H.
Published: May 2008

Abstract.We show that, under the Gaussian assumption of the white noise, the probability density function of a simple stationary first order bilinear process with ‘heterogeneous’ errors may be unbounded, whilst that with ‘homogeneous’ errors is always bounded. Simulation aspects of the distribution are also included.
A STATISTICAL APPROACH TO DIFFERENCE‐DELAY EQUATION MODELLING IN ECOLOGY–TWO CASE STUDIES1
Authors: Lim K. S. , Tong H.
Published: May 2008

Abstract.In the field of ecology, the importance of delay equations is well recognized. In the field of time series analysis, a new class of non‐linear models has been developed by Tong which exploits explicitly the notion of a delay and a threshold. In this paper, we demonstrate, with real ecological data, how the former may be used to motivate the latter, which in turn lends some support to the former. This paper represents a modest attempt in integrating ecological theory with time series practice.
DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS
Authors: McLeod A. I. , Li W. K.
Published: May 2008

Abstract.Squared‐residual autocorrelations have been found useful in detecting nonlinear types of statistical dependence in the residuals of fitted autoregressive‐moving average (ARMA) models (Granger and Andersen, 1978; Miller, 1979). In this note it is shown that the normalized squared‐residual autocorrelations are asymptotically unit multivariate normal. The results of a simulation experiment confirming the small‐sample validity of the proposed tests is reported.
THE ESTIMATION OF PARAMETERS FOR AUTOREGRESSIVE MOVING AVERAGE MODELS
Authors: Tuan Pham Dinh
Published: May 2008

Abstract. This paper provides some new and improved versions of an earlier procedure for the estimation of parameters for autoregressive moving average models suggested by the author (1979). Some numerical examples of the application of the procedure are also given.
A STUDY OF THE APPLICATION OF STATE‐DEPENDENT MODELS IN NON‐LINEAR TIME SERIES ANALYSIS
Authors: Haggan V. , Heravi S. M. , Priestley M. B.
Published: May 2008

Abstract.The theory of state‐dependent models was developed by Priestley (1980), and a few simple applications were given in Priestley (1981). In this paper, an extensive study of the application of state‐dependent models to a wide variety of non‐linear time series data is carried out. Both real and simulated data are used in the study, and the problems encountered are highlighted. The method is demonstrated to be successful in practice in many cases, and suggestions for the further development of the algorithm are also given.
A UNIFIED APPROACH TO ARMA MODEL IDENTIFICATION AND PRELIMINARY ESTIMATION
Authors: Piccolo D. , Wilson G. Tunnicliffe
Published: May 2008

Abstract.This paper reviews several different methods for identifying the orders of autoregressive‐moving average models for time series data. The case is made that these have a common basis, and that a unified approach may be found in the analysis of a matrix G, defined to be the covariance matrix of forecast values.

The estimation of this matrix is considered, emphasis being placed on the use of high order autoregression to approximate the predictor coefficients. Statistical procedures are proposed for analysing G, and identifying the model orders.

A simulation example and three sets of real data are used to illustrate the procedure, which appears to be a very useful tool for order identification and preliminary model estimation.
A KALMAN FILTER APPROACH TO THE FORECASTING OF MONTHLY TIME SERIES AFFECTED BY Morris Festivals
Authors: Morris N. D. , Pfeffermann D.
Published: May 2008

Abstract.Many economic time series are affected by the moving dates of festivals. In this paper a moving festival effect is defined and incorporated into a dynamic linear model which specifies how the parameters of several unobservable components of a time series evolve stochastically in time. The merits of this approach in comparison to other approaches are discussed and demonstrated using empirical data of three selected time series.
LEAST SQUARES ESTIMATES AND ORDER DETERMINATION PROCEDURES FOR AUTOREGRESSIVE PROCESSES WITH A TIME DEPENDENT VARIANCE
Authors: Tjøstheim Dag , Paulsen Jostein
Published: May 2008

Abstract.We study nonstationary autoregressive processes, where the variance of the generating white noise process is allowed to depend on time. It is shown that ordinary least squares estimates are strongly consistent and with a proper scaling factor asymptotically normal, but, as can be expected, they are not efficient. Furthermore, AIC type order determination criteria, used as if the underlying process is stationary, are consistent, whereas identification of order in terms of the partial autocorrelation function may lead one astray.
ADDITIVE ELEMENTS OF ARMA MODELS
Authors: Whittaker Joe
Published: May 2008

Abstract. The additive elements of the likelihood function (Whittaker, 1984) are a natural generalization of the regression elements of Newton and Spurrell (1967) and serve to simplify the analysis of several competing models. The aim of this note is to extend their application to time series analysis.
TRANSFER FUNCTION MODEL ORDER AND PARAMETER ESTIMATION
Authors: Lii Keh‐Shin
Published: May 2008

Abstract.A distributed lag model with a rational transfer function is considered. We have demonstrated that theC‐table can be used to determine the orders of the rational transfer function and the Padé table can be used to estimate the parameters of an identifiable transfer function. In case the model is not uniquely identified, theC‐table reduces possible competing models to only a few for further examination. Padé approximant gives consistent initial values for possibly more efficient iterative procedures to estimate the coefficients of the identified model. Some asymptotic results on the estimation of theC‐table and the Padé table are given. A few examples are presented to demonstrate the effectiveness of the method.
FORECASTING TIME SERIES:A COMPARATIVE ANALYSIS OF ALTERNATIVE CLASSES OF TIME SERIES MODELS
Authors: Cartwright Phillip A.
Published: May 2008

Abstract.Performance of the state dependent model developed by Priestley is evaluated relative to that of bilinear and standard linear models using two well‐known time series. The results indicate the use of broader classes of time series models beyond the conventional ARMA class is likely to lead to significant reductions in forecasting error. However, there are difficult problems relating to the identification of the order of the model, estimation of the parameters, and determination of the correct nonlinear model.