bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting for business planning: A case study of IBM product sales
Authors: Wu L. S.‐Y. , Ravishanker N. , Hosking J. R. M. 
Published: July 2007

AbstractThis is a case study of a closely managed product. Its purpose is to determine whether time‐series methods can be appropriate for business planning. By appropriate, we mean two things: whether these methods can model and estimate the special events or features that are often present in sales data; and whether they can forecast accurately enough one, two and four quarters ahead to be useful for business planning. We use two time‐series methods, Box‐Jenkins modeling and Holt‐Winters adaptive forecasting, to obtain forecasts of shipments of a closely managed product. We show how Box‐Jenkins transfer‐function models can account for the special events in the data. We develop criteria for choosing a final model which differ from the usual methods and are specifically directed towards maximizing the accuracy of next‐quarter, next‐half‐year and next‐full‐year forecasts. We find that the best Box‐Jenkins models give forecasts which are clearly better than those obtained from Holt‐Winters forecast functions, and are also better than the judgmental forecasts of IBM's own planners. In conclusion, we judge that Box‐Jenkins models can be appropriate for business planning, in particular for determining at the end of the year baseline business‐as‐usual annual and monthly forecasts for the next year, and in mid‐year for resetting the remaining monthly forecasts.
Conservatism and consensus‐seeking among economic forecasters
Authors: Batchelor Roy , Dua Pami 
Published: July 2007

AbstractThis paper uses the track records of a panel of US economic forecasters participating in a consensus forecasting service to test for conservatism and consensus‐seeking behaviour. The tests are based on a particular method‐of‐moments estimator, designed to allow for the heteroscedasticity and serial correlation which is inevitably present in errors from repeated forecasts for fixed target dates. Most forecasters prove to be conservative. When revising forecasts they give too much weight to their own past forecasts. Surprisingly, forecasters are not consensus‐seeking but ‘variety‐seeking’. When revising forecasts, they give too little weight to the known forecasts of other forecasters.
A note on diagrams for turning‐point diagnostics
Authors: Jarrell Stephen B. , Stanley T. D. 
Published: July 2007

AbstractA new diagram for discriminating a forecasting technique's history with respect to the two types of turning‐point errors, missed turns and false signals is presented. This diagram extends Theil's original prediction‐realization (P‐R) presentation so that each of the four quadrants and the axes locates a distinct type of forecasting error or correct forecast, thus reducing much of the former ambiguity. This improvement is accomplished without the loss of any information.
Structural adjustment in the UK and Europe under the ERM
Authors: Meen Geoffrey P. 
Published: July 2007

AbstractThe paper has three main objectives; first, to explore in more detail the properties of the OEF world model; second, to examine within the context of that model the process of structural adjustment in Europe since the establishment of the ERM and, third, to ask whether there are differences between the UK and the rest of Europe that might make the adjustment process to ERM membership difficult for the former. Differences in the housing market are highlighted.
Oil shocks: How can OECD countries manage them best?
Authors: Delessy Henri , Harasty Hélène 
Published: July 2007

AbstractAs the 1990‐91 Gulf crisis has emphasized, the risk of new oil shocks remains high in the medium to long run. Although energy intensity has decreased in the major countries since the first two oil shocks, the simulation performed with the MIMOSA world model, which is described in this paper, shows that a permanent rise in oil prices still induces direct strong negative consequences in the OECD: a temporary recession, a durable loss in production and employment and a lasting rise in inflation. Moreover, according to the model and due to national dissimilarities, an oil shock in Europe has some asymmetrical effects which are pointed out here. Further simulations test two different economic policy responses in the OECD: a ‘beggar‐thy‐neighbor’ policy in which each country tries to ‘export’ its unemployment by curbing domestic inflation and wage growth; and a co‐ordinated policy supporting both supply and demand. The first leads to a general deflationist overshooting. The second ensures stabilization with a much lower cost in employment.
ARIMA models of the price level: An assessment of the multilevel adaptive learning process in the USA
Authors: Dua Pami , Ray Subhash C. 
Published: July 2007

AbstractThis paper estimates the ARIMA processes for the observed and expected price level corresponding to the three‐level adaptive expectations model proposed by Jacobs and Jones (1980). These univariate processes are then compared with the best‐fit ARIMA model. The results indicate that the best‐fit model for the observed price level is a restricted version of the two‐level adaptive learning process specified in terms of prices, suggesting a simple adaptive rule in the inflation rate. A comparison of the time‐series forecasts from the best‐fit model with the mean responses to the ASA‐NBER survey shows no significant difference in their accuracy. The time‐series forecasts are, however, conditionally efficient. The best‐fit ARIMA model for expected prices measured by the ASA‐NBER consensus forecasts does not correspond to any version of the Jacobs and Jones model.
The dynamic and stochastic instability of betas: Implications for forecasting stock returns
Authors: Lin Winston T. , Chen Yueh H. , Boot John C. G. 
Published: July 2007

AbstractThe purpose of this paper is to simultaneously investigate several important issues that feature the dynamic and stochastic behavior of beta coefficients for individual stocks and affect the forecasting of stock returns. The issues include randomness, nonstantionarity, and shifts in the mean and variance parameters of the beta coefficient, and are addressed within the framework of variable‐mean‐response (VMR) random coefficients models in which the problem of heteroscedasticity is present. Estimation is done using a four‐step generalized least squares method. The hypotheses concerning randomness and nonstationarity of betas are tested. The time paths, sizes, and marginal rates of mean shifts are determined. The issue of variance shift is examined on the basis of five special tests, called T*, B, S', G and W. Then the impacts of the dynamic and stochastic instability on the estimation of betas is tested by a nonparametric procedure. Finally, the VMR models' ability of forecasting stock returns is evaluated against the standard capital asset pricing model. The empirical findings shed new light on the continuing debate as to whether the beta coefficient is random and nonstationary and have important implications for modeling and forecasting the measurement of performance and the determination of stock returns.
The maximum and minimum of primary forecasts
Authors: Cain M. , Law D. , Peel D. A. 
Published: July 2007

AbstractThe purpose of this paper is to suggest that the maximum (or minimum) of a number of primary forecasts may make a valuable addition to the forecasting accuracy of a combination of forecasts. Such forecasts are readily computable. Theoretical results are presented for two unbiased forecasts with correlated normally distributed errors, showing that the maximum (minimum) of two forecasts can have a smaller error variance than either of the primary forecasts and the forecast error can have low correlation with the primary errors. Empirical results are obtained for two different sets of forecasts available in the literature, and it is observed that a combination forecast including the maximum and/or minimum has attractive forecasting properties.
Modeling expert forecasting knowledge for incorporation into expert systems
Authors: Hamm Robert M. 
Published: July 2007

AbstractThe use of continuous multivariate models to represent experts' knowledge of relations among a set of variables is reviewed. Such knowledge models can be incorporated into expert systems, complementing contingent rules, especially when representing experts' knowledge of functional relations among entities in noisy domains. Past work has most commonly involved linear averaging models in static domains, although nonlinear models and dynamic domains are also possible. Detecting errors in continuous multivariate models requires a different approach from detecting errors in collections of if‐then rules. Methods for eliciting expert knowledge include modeling judgments made in real or hypothetical situations and using expert's self‐insight directly to assist in construction of the model. Procedures for managing each of these methods have been computerized and could be included as elicitation tools in expert system building environments.
Composite forecasts, non‐stationarity and the role of survey information
Authors: Holly S. , Tebbutt S. 
Published: July 2007

AbstractIn this paper, using composite predictors we examine whether the use of survey information on consumer confidence would have helped to predict fluctuations in economic activity. We also consider the implications of the new literature on time‐series modelling when the underlying processes are not stationary. We then examine what implications this has for the construction of composite predictors. We find that it is essential that any forecast—used as part of a composite predictor—is co‐integrated with the outcome. It is likely that this will hold in practice, but if it does not then the forecast errors will be non‐stationary and the interpretation of the composite predictor hazardous.
Forecast intervals of net migration: The case of the netherlands
Authors: Beer Joop De 
Published: July 2007

AbstractIn the Netherlands, as in many other countries, annual fluctuations in net migration are larger than those in births and deaths. As a result, forecasts of net migration are an important source of errors in population forecasts, particularly in the short run. In order to make it possible for the user to judge the usefulness of a population forecast, the forecaster should give an indication of the degree of uncertainty of the forecast of net migration. An ARIMA model can be used for specifying a statistical forecast interval. As the width of forecast intervals for migration in single years differs strongly from that of an interval for average migration during the forecast period, it is important that the forecaster indicates which type of interval is presented. A comparison of forecast intervals for net migration obtained from an ARIMA model to intervals in official Dutch national population forecasts shows that the uncertainty on migration has been underestimated in past official forecasts.
Discretization of stochastic differential equations and econometric forecasting: An application to time‐varying autoregressions
Authors: Neftci Salih N. 
Published: July 2007

AbstractContinuous time versions of time varying Vector Autoregressions are stochastic differential equations. Optimal discretization of Stochastic Differential Equations cannot be obtained by replacing all differentials by the corresponding first differences. In this paper we obtain the optimal discretization for time varying VARS. The results are applied to predicting the consumer price index.
A smart automated macroeconometric forecasting system
Authors: Moss Scott , Artis Michael , Ormerod Paul 
Published: July 2007

AbstractA smart, automated forecasting system is a kind of expert system for generating forecasts wholly or partly without human intervention. A pilot‐scale system is reported in this paper. The interventions are made by a rulebase which describes the actual intervention procedures of the London Business School Centre for Economic Forecasting on one of the major macroeconometric forecasting models for the U.K. economy. The rulebase is sufficiently general as to be applicable to any forecasting model. One difference of the pilot model reported in this paper from conventional models is that policy behaviour is described entirely by rules rather than equations. This allows the use of thresholds, floors, ceilings, and discontinuities.
Forecasting us home sales using bvar models and survey data on households' buying attitudes for homes
Authors: Dua Pami , Smyth David J. 
Published: July 2007

AbstractThis study uses Bayesian vector autoregressive models to examine the usefulness of survey data on households' buying attitudes for homes in predicting sales of homes. We find a negligible deterioration in the accuracy of forecasts of home sales when buying attitudes are dropped from a model that includes the price of homes, the mortgage rate, real personal disposable income, and die unemployment rate. This suggests that buying attitudes do not add much to the information contained in these variables. We also find that forecasts from the model that includes both buying attitudes and the aforementioned variables are similar to those generated from a model that excludes the survey data but contains the other variables. Additionally, the variance decompositions suggest that the gain from including the survey data in the model that already contains other economic variables is small.
An estimation model of figure segregation based on human visual perception
Authors: Shimaya Akira , Yoroizawa Isamu , Kosugi Makoto 
Published: July 2007

AbstractWhen observing an overlapped figure, a human tends to interpret the figure by decomposing it into simpler subfigures. In psychology, this attitude is called figure segregation. In general, an overlapped figure can be segregated in many ways, depending on the observer. In the engineering realization of the figure segregation, the frequency of selection for each segregation candidate must be estimated.Up to now, such factors as symmetry and continuity have been considered qualitatively as the factors affecting the decision about the segregation of the figure. This paper presents first a method to describe quantitatively those factors. Then the significance of the decision factor is determined by comparing the characteristic values of the decision factor in the segregation candidate and the selection frequency of that candidate in the psychological experiment. Furthermore, it is shown that the figure segregation characteristics can be estimated accurately, based on the prediction expression derived from the linear multiple regression analysis.
Analysis of the data concentration function of a four‐layer neural network in terms of the autoassociation and PPN models
Authors: Yonekura Tatsuhiro , Miyazaki Shin‐Ya , Toriwaki Jun‐Ichiro 
Published: July 2007

AbstractThis paper presents a systematic discussion of the relationship between classical multivariate analysis and various data compression methods arising from the nonlinear mapping capability of multilayer neural networks. The important points of a geometrical interpretation for the case of four or more layers are set down using the well known autoassociation model and the pulse‐input/pattern‐output network (PPN) model proposed by the authors. Next, the previously unused four‐layer autoassociative model is investigated and its effectiveness is demonstrated. Then, the four‐layer autoassociative mapping model and the four‐layer PPN are compared using a method based on multivariate analysis. That is, it is shown that each method can be related in an approximate fashion to piecewise‐linear data compression models as well as to factor analysis models. Finally, to back up these studies, several example experiments are described; a five‐layer autoassociative mapping model is then examined, and the data compression capabilities of all three models are compared.
Progressive coding of color‐quantized images
Authors: Kumazawa Hiroyuki , Tomita Satoru 
Published: July 2007

AbstractProgressive coding of color‐quantized images, a technique that allows a progressive increase in the number of image colors transmitted, is described. In most color‐quantized image coding techniques, the representative colors are assigned indices that bear no logical relationship to them. In this paper, algorithms that assign indices logically related to the representative colors are presented and it is shown that bitplane transmission with the indices assigned in this manner allows progressive transmission of color‐quantized images. Two coding algorithms are proposed: runlength coding of independent bitplanes and predictive coding based on the correlation between neighboring pixels and on interbitplane correlation. The coding efficiencies of the two methods for various kinds of color‐quantized images are evaluated. Predictive coding can reduce entropy by 10 percent for photographic images and by 30 percent for computer graphic images.
Construction of an environment model with sequential stereo images
Authors: Tsudo Akihiro , Yachida Masahiko 
Published: July 2007

AbstractThis paper proposes a sequentially updated environment model for a mobile robot equipped with a stereo camera. Information obtained from the visual sensors on the robot is used to construct a model for the area surrounding the path of the robot. The model is sequentially updated as environmental data is acquired, and relationships between multiple image frames are observed. The principle of trinocular stereo is applied to the sequential images occurring before and after movement. Line segments are constructed on the frames showing spatial and temporal relationships, and from these, a three‐dimensional geometric wire‐frame model is constructed. The model also uses efficient relationships to allow rapid processing and continual updating of the model.
A test‐path determination method based on define‐use chains: Test conditions and program fault overlooks
Authors: Nakajo Takeshi , Yamaguchi Ichiro , Kume Hitoshi 
Published: July 2007

AbstractWhen selecting the set of conditions to be tested in modular white‐box testing of fundamental program functions, various kinds of criteria are available, including the branch coverage criterion and the all‐uses criterion. But there has been very little research on the relationship of these criteria to the overlooking of program faults, and as a consequence many program faults have been discovered only in the later phases of development or at customer sites, where conditions not covered by the original testing occurred. In this paper, an attempt is made to identify the relationship between test conditions and program fault overlooks by expressing the data flows of the program as chains of define‐use relationships between two variables. The approach is tested on commercial software products for the control of measuring equipment. The results are used to develop a method of choosing test paths so as to prevent the principal overlook types, and the detection ability and computational efficiency are compared with those of conventional selection criteria. The number of tests required in the new method is comparable with that in the all‐uses method, and it is capable of preventing almost all of the overlooks that arise from the method used for test path selection.
Design of testing circuit and test generation for built‐in current testing
Authors: Miura Yukiya , Wada Yasushi , Kinoshita Kozo 
Published: July 2007

AbstractRecently current testing is beginning to be noticed as a testing method for CMOS circuits. However, since CMOS circuits cause the dynamic current due to switching, it has been pointed out that testing at a fast clock rate by current testing is difficult. To cope with this problem a built‐in current testing circuit is proposed in this paper. It is a circuit which measures the value of the dynamic current integrated over a unit time. Next a test sequence generation method for the proposed circuit is presented. In this method test sequences are generated so that the numbers of changes in the gate output values for two consecutive test vectors are almost equal. As a result the dynamic current does not change much between consecutive vectors. Finally the results of test generation for ISCAS'85 benchmark circuits are shown.
Magnetic field imaging using ct technique — roi reconstruction system
Authors: Saito Hideo , Fujita Ken'Ichi , Makajima Masato 
Published: July 2007

AbstractThis paper proposes a method to visualize the spatial distribution of the magnetic field in the region of interest (ROI), using CT technique. An experimenal system is constructed to visualize the magnetic field in ROI. In the reconstruction of the distribution in general by the CT technique, the projection data should not contain data outside the region of reconstruction. In the visualization of the magnetic field by CT techniques proposed up to the present, however, the projection data containing the magnetic field distribution outside the region of reconstruction are contained in the measurement. Consequently, the technique has been applied only to the case where the magnetic field exists only inside ROI.This paper proposes the following method. Wires for detecting the magnetic field are placed in the region of reconstruction. It is noted that the projection data obtained from the induced voltage does not contain the magnetic field distribution outside the region of reconstruction. This property is utilized in the visualization of the magnetic field distribution in the region of reconstruction.This paper describes also the principle of the fore‐mentioned methods, as well as the ROI visualization system constructed based on the principle. Using the proposed method, result of visualization is shown for magnetic field distribution produced by a permanent magnet.
PQL: Modal logic for compositional verification of concurrent programs
Authors: Uchihira Naoshi 
Published: July 2007

AbstractThe temporal logic model checking method is very useful for verification of concurrent programs that can be expressed by finite state transition systems. However, a major drawback to using this method is that as the scale of the programs increases, the computation costs for verification increase exponentially. An effective solution for this problem is compositional verification. Compositional verification is a method in which the bisimulation equivalence of concurrent programs is used to extract from each construction element (subprocess) only that abstract information necessary to verify each query, thereby avoiding an explosion in cost.In this paper, PQL (Process Query Language) is proposed as an improved method in the solution of this problem. PQL is based on modal logic which is the union of temporal and process logic. Also in this paper, the compositional verification method is proposed by using PQL with consideration of the “divergence by internal transition”.