bluuebunny/crossref_metadata_2025_split huggingface dataset:
PROPERTIES OF THE PATTERNED VECH OPERATOR
Authors: McGilchrist C.A. , Cullis B.R. 
Published: February 2008

SummaryThe vec operator arranges the columns of a matrix one below the other. When the matrix is symmetric such elements are not distinct but an extraction of only the distinct elements on or below the diagonal forms the operation denoted by vech. For other types of patterned matrices a ‘patterned vech’ operator is defined. The transformations from vech to vec are not uniquely defined. Here we examine properties of linear transformations which overcome the lack of uniqueness and develop properties of such linear transformations.
A SIMPLE SEQUENTIAL WILCOXON TEST
Authors: Phatarfod R.M. , Sudbury Aidan 
Published: February 2008

SummaryA simple sequential non‐parametric test for the two‐sample problem is proposed. A method of deriving its O.C. and A.S.N. funtions is given, and their adequacy confirmed by simulation. The test is found to require about 10 percent more observations than an optimal rank test; however it is much easier to apply. The test is found to be relatively robust.
VARIANCE ESTIMATION IN MULTI‐STAGE SAMPLING
Authors: Arnab R. 
Published: February 2008

SummaryIn multi‐stage sampling with the first stage units (fsu) chosen without replacement (WOR) with varying probability schemes (VPS) unbiased estimators (UE) of variances of homogeneous linear (HL) functions of unbiased estimators (UE) Ti's of fsu totals Yi's based on selection of subsequent stage units (SSU) from chosen fsu's are derived as homogeneous quadratic (HQ) functions of alternative less efficient UE's, say of Ti';'s of Yi's. Specific strategies are illustrated.
ASYMPTOTIC OPTIMALITY OF LIKELIHOOD RATIO TESTS FOR EXPONENTIAL DISTRIBUTIONS UNDER TYPE II CENSORING
Authors: Kourouklis Stavros 
Published: February 2008

SummaryConsider the model of k two parameter exponential populations under a type II censoring scheme. In this paper we establish optimality in the sense of Bahadur of the likelihood ratio test for an arbitrary testing problem by requiring only Condition A in Hsieh (1979). This result unifies and generalizes the results in Samanta (1986).
KENDALL'S TAU AND CONTINGENCY TABLES
Authors: Brown B.M. 
Published: February 2008

SummaryKendall's tau is a coefficient of concordance between two rankings of n objects. Its definition and large sample normal approximation are easily extended to the case where one of the rankings contains ties. In this paper, definition and normal approximation are extended further to the case where both rankings contain ties. The results are applied to give a fully distribution‐free test for two‐way contingency tables with ordered categories.
A NOTE ON MULTIVARIATE LINEAR MODELS WITH NON‐ADDITIVITY
Authors: Kshirsagar Anant M. 
Published: February 2008

SummaryTukey's non‐additivity test in an analysis of variance model is extended to a multivariate linear model with covariates. If non‐additivity is found to exist, a Wilks's Lambda test for the dimensionality of the matrix of the non‐additivity parameters is derived and the Lambda criterion is then factorized into two independent test criteria to test meaningful hypotheses concerning the multivariate model.
INFERENCE ABOUT THE MEAN OF A POISSON DISTRIBUTION IN THE PRESENCE OF A NUISANCE PARAMETER
Authors: Yip Paul 
Published: February 2008

SummaryIn this note we examine the problem of estimating the mean of a Poisson distribution when a nuisance parameter is present. Using a condition of Cox (1958) about ancillarity in the presence of a nuisance parameter, we justify that inference about the parameter should be carried out using the conditional distribution given the appropriate ancillary statistics. A small simulation study has been done to compare the performance of the conditional likelihood approach and the standard likelihood approach.
THE REDUCTION OF RISKS FOR SET‐VALUED ESTIMATORS
Authors: Meister H. , Moeschlin O. 
Published: February 2008

SummaryAn extension of the Theorem of Rao‐Blackwell will be given for the case of set‐valued estimators, its images being nonempty, compact‐convex subsets of a certain Banach space. Moreover sufficiency will be characterized in connection with set‐valued estimators by related point‐valued functions.
THE UNEMPLOYMENT RATE WHEN THE LABOUR MARKET IS MODELLED BY A MARKOV CHAIN
Authors: Klebaner Fima C. 
Published: February 2008

SummaryAssuming a Markov chain model for the labour market flow, we study it in its equilibrium state, We compare the observed and the theoretical unemployment rates. It is found that the observed unemployment rate approximates very closely the theoretical one. The mean and variance of the observed unemployment rate are computed. It is shown that its asymptotic distribution is normal.
JACKKNIFE TESTS FOR HETEROSCEDASTICITY IN THE GENERAL LINEAR MODEL
Authors: Giaccotto Carmelo , Sharma Subhash C. 
Published: February 2008

SummaryIn this paper, tests based on the Jackknife technique are proposed to test for heteroscedasticity in the linear regression model when the errors are non‐normal. These are the Jackknifed Goldfeld‐Quandt (GQ), and jack‐knife related variations of White (H), Lagrange multiplier (LM), Glejser (GL) and Bickel (B) tests. The power of the proposed tests is compared with that of GQ, H, LM, GL and B tests; and the robustness to the error distribution is analyzed under several heteroscedastic assumptions. The GQ test is by far the best test if the error distribution is close to normal, however, GQ test is not robust against non‐normal errors. By applying the jackknife technique to the regression a more robust statistic (GQJRG) is produced but the cost is a loss in power. The GQJRG statistic generally is not M powerful as the Bickel (BlOLS) and Glejser (GLlOLS) statistics.
DELAY ESTIMATION BY A HILBERT TRANSFORM METHOD
Authors: Nakano Junji , Tagami Shigemi 
Published: February 2008

SummaryThis paper describes an estimation of the time delay between two stationary time series signals, in which an input signal is measured with little noise and an output signal is the sum of a noise and the response from a linear system. We use the Hilbert transform relation for minimum delay systems to estimate the time delay. Some computer simulation results are given to evaluate the performance of the proposed method.
ESTIMATION OF THE CONDITIONAL PROBABILITY OF TUBERCULOSIS GIVEN THE RESPONSE OF A MANTOUX TEST
Authors: Hannah Murray , Becker Niels , Rich Jacob , Castle Charles 
Published: February 2008

SummaryFor the planning of community tuberculosis, prophylaxis one must know the prevalence of tuberculosis (TB) infection as a function of response to the Mantoux intradermal tuberculin test; the standard test for indicating Mycobacterium TB infection. The skin induration size used to select individuals for prophylaxis must be chosen carefully, in view of the costs associated with carrying out and supervising such prophylaxis.The Mantoux test was used to obtain measurements on adolescents in metropolitan Victoria and on a small sample of adolescents with clinical TB. These data are employed to obtain estimates and to construct upper confidence bounds for the conditional probability of TB infection, given the level of Mantoux response. Two conservative methods are presented; one is ‘nonparametric’, the other ‘semiparametric’. The analyses indicate that for responses up to and including 13 mm, the probability of TB infection is less than.07 with ninety‐five percent confidence.
DECOMPOSITIONS FOR CONDITIONAL SYMMETRY MODEL INTO PALINDROMIC SYMMETRY AND MODIFIED MARGINAL HOMOGENEITY MODELS
Authors: Tomizawa Sadao 
Published: February 2008

SummaryFor square contingency tables with ordered categories, the conditional symmetry model is decomposed into the palindromic symmetry and the modified marginal homogeneity models, and moreover into the generalized palindromic symmetry model and two other models. The data on unaided vision first analysed by Stuart (1953, 1955) is analysed again by using the decompositions.
ON EMPIRICAL BAYES STOPPING TIMES
Authors: Karunamuni Rohan 
Published: February 2008

SummaryWe consider the empirical Bayes decision theory where the component problems are the optimal fixed sample size decision problem and a sequential decision problem. With these components, an empirical Bayes decision procedure selects both a stopping rule function and a terminal decision rule function. Empirical Bayes stopping rules are constructed for each case and the asymptotic behaviours are investigated.
UNBIASED ESTIMATION OF PARAMETRIC FUNCTIONS IN SAMPLING FROM TWO ONE‐TRUNCATION PARAMETER FAMILIES
Authors: Rohatgi Vijay K. 
Published: February 2008

SummaryWe consider the problem of minimum variance unbiased estimation of a U‐estimable function of two unknown truncation parameters based on independent random samples from two one‐truncation parameter families. In particular, we obtain the UMVU estimator of the probability that Y > X.
A SEQUENTIAL METHOD OF CONSTRUCTING OPTIMAL BLOCK DESIGNS
Authors: Zergaw Getachew 
Published: February 2008

SummaryAn algorithm for the construction of a wide class of block designs including Balanced Incomplete Blocks (BIB) is described. The algorithm which allows the experimenter to give weights for a set of treatment contrasts uses an initial starting design to generate an optimal block design sequentially. The performance of the algorithm is illustrated by examples, and designs constructed by the algorithm compare favourably with designs generated by other methods.
A REMARK ON TESTING SIGNIFICANCE OF AN OBSERVED CORRELATION MATRIX
Authors: And Shande Chen , Mudholkar Govind S. 
Published: February 2008

summaryA simple test for the diagonality of the covariance matrix of a multi‐variate normal population is proposed. The test, which is based upon the sum of squares of the z‐transforms of the sample correlations, is seen to compare well with the current tests in terms of both the null distribution approximations and the powers.
A RENEWAL THEOREM IN MULTIDIMENSIONAL TIME
Authors: Hagwood Charles 
Published: February 2008

summaryLet Yl, Y2,… be i.i.d., positive, integer‐valued random variables with means, μ. Let the sequences {Yij, j= 1,2,…}, i= 1,…, r be independent copies of {Y1, Y2,…}. For n={n1,…, nr.}, n1≥1, let Sn=S̀n1k1=1= 1 …S̀nrkr=1 Yik1… Yrkr. We show that S̀Nk=1S̀∞k1=1…S̀∞nr=1 P[[Sn= k] ˜ [μ‐r N logr‐1 (N)/(r‐1)!] as N →∞.
THE SIGN TEST FOR STOCHASTIC PROCESSES
Authors: Huggins R.M. 
Published: February 2008

summaryIt is shown that the sign test may be applied to the residuals from the use of model fitting procedures, such as conditional least squares, to make inferences on the predictable part of a stochastic process. Minimal assumptions on the distribution of the process, apart from those already required for the model fitting procedure, are needed. The results are illustrated with an application to first order autoregressive processes.
ON THE EFFICIENCY OF THE QUASI‐LIKELIHOOD ESTIMATORS FOR EXPONENTIAL FAMILIES WITH EXTRA VARIATION
Authors: Morton R. 
Published: February 2008

summaryBounds are obtained for the asymptotic efficiency of the quasi‐likelihood estimator relative to the likelihood estimators for exponential families with random variables in the exponent. We conclude that the quasi‐likelihood is very efficient in the Poisson case for small means or small extra variation.
CONCOMITANT SCALE ESTIMATION IN REGRESSION PROBLEMS WITH INCREASING DIMENSION
Authors: Welsh A.H. 
Published: February 2008

summaryWe obtain Bahadur representations for the semi‐interquartile range and the median deviation when these estimators are based on the residuals from a linear regression model with increasing dimension. These representations yield a variety of central limit theorems and conditions under which the two estimators are equivalent. In particular, the representations justify the use of the estimators as concomitant scale estimators in general scale equivariant M‐estimation of a regression parameter when the dimension of the parameter increases with the sample size.
SOCIOECONOMIC INFLUENCES ON EDUCATIONAL Attainment: EVIDENCE And IMPLICATIONS FOR THE TERTIARY EDUCATION FINANCE DEBATE
Authors: Miller Paul , Volker Paul 
Published: February 2008

AbstractExamination of educational continuation decisions from Year 10 to tertiary entrance indicates that the major decision point appears to be at the end of Year 10. This is true even for persons entering tertiary education. Policies aimed at altering the social composition of high school graduates or tertiary sector participants should therefore be aimed at the Year 10 threshold or at even earlier stages in the educational process. However, as differences in participation in education amongst various socioeconomic groups appear to reflect differences in attitudes rather than purely financial factors, it may be difficult for authorities to expand school retention in the short term.
WHAT DRIVES AUSTRALIAN TEENAGE LABOUR FORCE PARTICIPATION?
Authors: Larum John , Beggs John J. 
Published: February 2008

SummaryThis paper examines the disaggregated components of Australian teenage labour force participation rates for males and females, for part‐time and full‐time participants and for those still at school. The paper also examines school participation rates for the same group of teenagers. Data are analysed for the period 1978 quarter 1 to 1987 quarter 2. In line with previous research, labour market demand factors are found to be major explanators of participation rates, but supply side effects due to the government's secondary school student allowance and also unemployment benefits are found to be important determinants of work and schooling decisions.
MODELLING OF TRANSITIONS BETWEEN EMPLOYMENT STATES FOR YOUNG AUSTRALIANS
Authors: Dunsmuir William , Tweedie Richard , Flack Lloyd , Mengersen Kerrie 
Published: February 2008

SummaryThis paper reports results from modelling the employment state calendars merged from the Australian Longitudinal Survey's 1985 and 1986 Area Samples. A semi‐Markov model is proposed for the transitions between the three employment states: employed, unemployed and not‐in‐the‐labour‐force.Sojourn times in each of the states are fitted by the non‐parametric maximum likelihood methods proposed by Dinse & Larsen (1986), as are probabilities of transition between states. These models contrast with existing work where, typically, only the unemployment state is modelled and where unemployment times are fitted by parametric means.The richness of the ALS data enables us to take in sex, age and educational attainment factors at two levels each by use of cohorts rather than by parametric models.We show that age and education both play a significant role in duration of employment and unemployment. We also show that the initial state sampled (which will often be the first event post‐schooling) may be different from the other events to a much greater degree than length‐biasing would indicate.We find that there is a significant “hard‐core” of unemployed and employed, and that a Weibull model fits the data well after this effect is taken out.
ON TESTING AGAINST RESTRICTED ALTERNATIVES FOR THE VARIANCES OF GAUSSIAN MODELS
Authors: Adegboye O. Sola , Gupta A.K. 
Published: February 2008

SummaryLet π1,…,πp be p independent normal populations with means μ1…, μp and variances σ21,…, σ2p respectively. Let X(ni) be a simple random sample of size ni from πi, i = 1,…,p. Given the simple random samples X(n1),…, X(np) from π1,…,πp respectively, a test has been proposed for testing the homogeneity of variances H0: σ21=…σ2p, against the restricted alternative, H1: σ21≥…≥σ2p, with at least one strict inequality. Some properties of the test are discussed and critical values are tabulated.
OPTIMAL DESIGNS FOR FITTING A PROPORTIONAL HAZARDS REGRESSION MODEL TO DATA SUBJECT TO CENSORING
Authors: Becker Niels , McDonald Barry , Khoo Celestine 
Published: February 2008

SummarySuppose the probability model for failure time data, subject to censoring, is specified by the hazard function λ(t)exp(βT x), where x is a vector of covariates. Analytical difficulties involved in finding the optimal design are avoided by assuming that λ is completely specified and by using D‐optimality based on the information matrix for β Optimal designs are found to depend on β, but some results of practical consequence are obtained. It is found that censoring does not affect the choice of design appreciably when βT x ≥ 0 for all points of the feasible region, but may have an appreciable effect when βixi 0, for all i and all points in the feasible experimental region. The nature of the effect is discussed in detail for the cases of one and two parameters. It is argued that in practical biomedical situations the optimal design is almost always the same as for uncensored data.
ON THE UNIMODALITY OF TRANSITION PROBABILITIES IN MARKOV CHAINS
Authors: Kijima Masaaki 
Published: February 2008

SummaryConsider a discrete time Markov chain X(n) denned on {0,1,…} and let P be the transition probability matrix governing X(n). This paper shows that, if a transformed matrix of P is totally positive of order 2, then poj(n) and pio(n) are unimodal with respect to n, where pij(n) = Pr[X(n) = j |X(0) = i]. Furthermore, the modes of poj(n) and pio(n) are non‐increasing in j and I, respectively, when additionally P itself is totally positive of order 2. These results are transferred to a class of semi‐Markov processes via a uniformization.
AN ALGORITHMIC APPROACH TO BAYESIAN LINEAR MODEL CALCULATIONS
Authors: Carlin J.B. 
Published: February 2008

SummaryA framework is described for organizing and understanding the computations necessary to obtain the posterior mean of a vector of linear effects in a normal linear model, conditional on the parameters that determine covariance structure. The approach has two major uses; firstly, as a pedagogical tool in the derivation of formulae, and secondly, as a practical tool for developing computational strategies without needing complicated matrix formulae that are often unwieldy in complex hierarchical models. The proposed technique is based upon symbolic application of the sweep operator SWP to an appropriate tableau of means and covariances. The method is illustrated with standard linear model specifications, including the so‐called mixed model, with both fixed and random effects.
TEACHING STATISTICS: A TALK ABOUT TIME SERIES
Authors: Anderson Oliver D. 
Published: February 2008

SummaryWhen presenting research results to a mixed audience, it is common for seminar speakers either to address the specialists or the uninitiated (thus alienating the other, uncatered‐for group of listeners), or to risk falling between these two stools (and so satisfy no one). We suggest a way that the lecturer's dilemma might often be more optimally resolved; and, in so doing, present material which could provide useful ideas for wider application in enlivening formal class‐room instruction in time‐series analysis. Finally, we pre‐empt some of the predicted response that the content of this paper may trigger from certain experts; and discuss the general lack of emphasis on assumptions in statistical teaching.
A MARKOV CHAIN MODEL FOR MAGAZINE EXPOSURE
Authors: Danaher Peter J. 
Published: February 2008

SummaryKlotz's (1973) Markov chain model for dependent Bernoulli trials is applied to magazine exposure distributions. Simple parameter estimates are derived and are shown to compare well with the maximum likelihood estimates. The Markov model is fitted to forty magazines from a large print media survey and compares favourably with the most popular non‐proprietary magazine model, the beta‐binomial model. In addition, the Markov model is used to simulate magazine exposure distributions.
COVARIANCES FOR FIXED INTERVAL SMOOTHED KALMAN FILTER PARAMETER ESTIMATES
Authors: Haslett Stephen 
Published: February 2008

SummaryGiven time series data for fixed intervalt= 1,2,…,Mwith non‐autocorrelated innovations, the regression formulae for the best linear unbiased parameter estimates at each timetare given by the Kalman filter fixed interval smoothing equations. Formulae for the variance of such parameter estimates are well documented.However, formulae for covariance between these fixed interval best linear parameter estimates have previously been derived only for lag one. In this paper more general formulae for covariance between fixed interval best linear unbiased estimates at timestandt ‐ lare derived fort= 1,2,…,Mandl= 0,1,…,t‐ 1. Under Gaussian assumptions, these formulae are also those for the corresponding conditional covariances between the fixed interval best linear unbiased parameter estimates given the data to timeM.They have application, for example, in determination via the expectation‐maximisation (EM) algorithm of exact maximum likelihood parameter estimates for ARMA processes expressed in statespace form when multiple observations are available at each time point.
A NEW UPPER BOUND FOR THE EFFICIENCY FACTOR OF A BLOCK DESIGN
Authors: Tjur Tue 
Published: February 2008

SummaryAn upper bound for the efficiency factor of a block design, which in many cases is tighter than those reported by other authors, is derived. The bound is based on a lower bound for E(1/X) in terms of E(X) and var(X) for a random variableXon the unit interval. For the special case of resolvable designs, an improved bound is given which also competes with known bounds for resolvable designs in some cases.
LOSS OF INFORMATION ASSOCIATED WITH THE ORDER STATISTICS AND RELATED ESTIMATORS IN THE DOUBLE EXPONENTIAL DISTRIBUTION CASE
Authors: Akahira Masafumi , Takeuchi Kei 
Published: February 2008

SummaryFisher (1934) derived the loss of information of the maximum likelihood estimator (MLE) of the location parameter in the case of the double exponential distribution. Takeuchi & Akahira (1976) showed that the MLE is not second order asymptotically efficient. This paper extends these results by obtaining the (asymptotic) losses of information of order statistics and related estimators, and by comparing them via their asymptotic distributions up to the second order.
A ROLE FOR VARIOGRAMS
Authors: Robinson G.K. 
Published: February 2008

SummaryIn time series texts and journals, variograms are mentioned seldom, if at all. The autocovariance function is preferred. However there are situations where the variogram can be estimated with moderate precision but the autocovariance function cannot, because the variance of the process is not well known. If the problem to be solved does not require the process variance for its solution then it is generally more straightforward to use the variogram rather than the autocovariance function in solving this problem.
A CLASS OF NONPARAMETRIC TESTS FOR THE ONE‐SAMPLE LOCATION PROBLEM
Authors: Mehra K.L. , Prasad N.G.N. , Rao K.S. Madhava 
Published: February 2008

SummaryA class of “optimal”U‐statistics type nonparametric test statistics is proposed for the one‐sample location problem by considering a kernel depending on a constant a and all possible (distinct) subsamples of size two from a sample of n independent and identically distributed observations. The “optimal” choice of a is determined by the underlying distribution. The proposed class includes the Sign and the modified Wilcoxon signed‐rank statistics as special cases. It is shown that any “optimal” member of the class performs better in terms of Pitman efficiency relative to the Sign and Wilcoxon‐signed rank statistics. The effect of deviation of chosen a from the “optimal” a on Pitman efficiency is also examined. A Hodges‐Lehmann type point estimator of the location parameter corresponding to the proposed “optimal” test‐statistics is also defined and studied in this paper.