bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interval estimates for diatom‐inferred lake pH histories
Authors: Oehlert Gary W. 
Published: June 2006

AbstractWe investigate ordinary least‐squares and Bayesian methods for constructing interval estimates for historical lake pH's inferred from diatom sediments. The Bayesian method explicitly models several forms of variability, including the sampling and classification variability of the diatom records, estimation variability, and measurement error in observed pH's. The two methods produce similar interval estimates, but the Bayesian model allows design recommendations to be made.
Change‐over designs with complete balance for first and second residual effects
Authors: Sharma V.K. 
Published: June 2006

AbstractThis paper presents a unified method of constructing change‐over designs that permit the estimation of direct effects orthogonal to all other effects when the residual effects of treatments last for two consecutive periods. Explicit methods of analysis of these designs have been obtained for the situations where the first period observations are omitted from the analysis and where the first period observations are included.
The random robin problem for laplace's equation
Authors: Becus Georges A. 
Published: June 2006

AbstractA random generalized solution to the Robin problem for Laplace's equation is defined in terms of the sections of the random boundary data. Existence, uniqueness, and properties are established for such a solution. Particularizations to the Dirichlet and Newmann problems as well as generalization to the Robin‐Poisson problem are mentioned. Applications of the results are provided.
The mean and variance of rank and exponential score product moment statistics in the non‐circular case
Authors: Rodden B. E. , Landolt J. P. 
Published: June 2006

AbstractThis paper gives a general formula for the first two moments of the non‐circular product moment statistic, which is used as a test for the statistical independence of the interarrival times of certain time series data, e.g., neuronal spike discharges. For the special cases of rank and exponential score product moment statistics, the mean and variance are formulated.
Bounds for moments through a general orthogonal expansion in a pre‐hilbert space‐I
Authors: Mathai A. M. 
Published: June 2006

AbstractBounds are obtained for the product moments of an arbitrary finite number of ordered random variables. These bounds are obtained with the help of a representation of an arbitrary function in terms of a complete orthonormal system in a pre‐Hilbert space of square integrable functions defined in a k‐dimensional unit cube.
Multiparameter estimation of discrete exponential distributions
Authors: Tsui Kam‐Wah 
Published: June 2006

AbstractLetX1, …,Xpbe independent random variables, all having the same distribution up to a possibly varying unspecified parameter, where each of thepdistributions belongs to the family of one parameter discrete exponential distributions. The problem is to estimate the unknown parameters simultaneously. Hudson (1978) shows that the minimum variance unbiased estimator (MVUE) of the parameters is inadmissible under squared error loss, and estimators better than the MVUE are proposed. Essentially, these estimators shrink the MVUE towards the origin. In this paper, we indicate that estimators shifting the MVUE towards a point different from the origin or a point determined by the observations can be obtained.
Estimation of poisson means under weighted squared error loss
Authors: Tsui Kam‐Wah 
Published: June 2006

AbstractIn estimating the means of several independent Poisson distributions, we show that the maximum likelihood estimator is inadmissible when general weighted squared error loss is the criterion. Using this result, we extend the known results on estimation of several Poisson means (Peng 1975, Hudson 1978) to the case where possibly more than one observation is taken from each Poisson distribution and the samples are not necessarily of the same size.
Tests based on equivariant estimators
Authors: Rivest Louis‐Paul 
Published: June 2006

AbstractLet Ť(1) and Ť(2) be location‐equivariant estimators of an unknown location parameter μ. It is shown that the test for H0: μ ≤ μ0 versus HA : μ > μ0 that rejects H0 if Ť(1) is large is uniformly more powerful than the one that rejects H0 if Ť(2) is large if and only if Ť(2) is “more dispersed” than Ť(1). A similar result is obtained for tests on scale using the star‐shaped ordering. Examples are given.
On Khatri's characterization of the inverse‐Gaussian distribution
Authors: Letac GÉRard , Seshadri Vanamamalai 
Published: June 2006

AbstractKhatri has given a characterization of the inverse‐Gaussian distribution by the independence of two statistics. His proof involves assumptions on the existence of certain moments. In this note, we offer a short proof using only the positivity of the random variable X1.
Mixtures, embedding, and ancillarity
Authors: Evans M. , Fraser D. A. S. , Monette G. 
Published: June 2006

AbstractAncillary statistics, proposed by Fisher (1925), can be constructed by forming amixture model(Birnbaum 1962) or can be extracted or derived from atransformation‐parameter model(Peisakoff 1951, Fraser 1961) or from the corresponding error‐basedstructural model(Fraser 1968, 1979); these latter models involve an implicitmixturestructure. Compound models with ancillaries can also be formed by a crossembedding, discussed from a technical viewpoint in this paper. Of the 25 examples in Buehler (1982), 22 are mixtures or implicit mixtures and 3 correspond to cross embedding. The cross embedding examples exemplify the nonuniqueness difficulties with ancillaries. This paper discusses a simple and two generalized versions of cross embedding but makes no general valuations of these for statistical inference; their role within inference is discussed in Evans, Fraser, and Monette (1984, 1985).
Analyzing cross‐sectional and longitudinal lung‐function measurements: The effects of age
Authors: Schulzer Michael , Enarson Donald A. , Chan‐Yeung Moira 
Published: June 2006

AbstractThe problem of interpreting lung‐function measurements in industrial workers is examined. The data under discussion pertain to FEV1 and FVC measurements in smoking and in nonsmoking groups of grain‐elevator workers in British Columbia and of workers in Vancouver City Hall. Initial observations have now been enriched by longitudinal follow up data on the same groups after three and after six years. It is shown that interesting selection phenomena, favouring “fit” individuals, take place over time, with regard both to lung symptoms and lung functions. Thus cross‐sectional and longitudinal studies refer to somewhat different populations. It also appears that longitudinal studies are considerably more sensitive to identifying cumulative lung damage than are corresponding cross‐sectional studies. The nonlinearity of the effect of age on lung functions is noted in the longitudinal data in a number of cases, lending support to the hypothesis of association between quadratic age effect and cumulative exposure to lung insults.
Testing whether new is better than used of a specified age, with randomly censored data
Authors: Hollander Myles , Park Dong Ho , Proschan Frank 
Published: June 2006

AbstractUsing randomly censored data, we develop a test of the null hypothesis that a new item has stochastically the same residual lifelength as does a used item of specified age t0, versus the alternative hypothesis that a new item has stochastically greater residual lifelength than does a used item of age t0. We also compare our test with a related test, developed for a complete‐data model, in order to study the loss in efficiency because of censoring.
Quadratic nuisance‐parameter‐free goodness‐of‐fit tests in the presence of location and scale parameters
Authors: Aly Emad‐Eldin A. A. , CsÖ MiklÓS 
Published: June 2006

AbstractThe asymptotic theory of a quadratic nuisance‐parameter‐free goodness‐of‐fit procedure is studied. The present techniques are applied in testing for the exponential, the logistic, the extreme value, and the Weibull distributions.
Equally spaced design points in polynomial regression: A comparison of systematic sampling methods with the optimal design of experiments
Authors: Bellhouse David R. , Herzberg Agnes M. 
Published: June 2006

AbstractIn some situations an experimenter may desire to have equally spaced design points. Three methods of obtaining such points on the interval [—1,1]—namely systematic random sampling, centrally located systematic sampling, and a purposive systematic sampling method which includes the endpoints ‐ 1 and 1 as two of the design points‐are evaluated under the D‐optimal and G‐optimal criteria. These methods are also compared to the optimal designs in polynomial regression and to the limiting designs of Kiefer and Studden (1976).
Bayes and empirical Bayes shrinkage estimation of regression coefficients
Authors: Nebebe Fassil , Stroud T. W. F. 
Published: June 2006

AbstractFor a moderate or large number of regression coefficients, shrinkage estimates towards an overall mean are obtained by Bayes and empirical Bayes methods. For a special case, the Bayes and empirical Bayes shrinking weights are shown to be asymptotically equivalent as the amount of shrinkage goes to zero. Based on comparisons between Bayes and empirical Bayes solutions, a modification of the empirical Bayes shrinking weights designed to guard against unreasonable overshrinking is suggested. A numerical example is given.
Predictive densities and selection with genetic applications
Authors: Tallis G. M. 
Published: June 2006

AbstractA set ofppopulations is subjected to a first sampling. From this, it is required to select one of the populations so that the mean of a future sample is maximized. Extensions to this problem are discussed and solved by the use of predictive densities. These results are finally adapted to populations with covariate structure under systems of balanced sampling. Applications to quantitative genetics are indicated.
Single‐parameter inference based on partial prior information
Authors: Lambert Diane , Duncan George T. 
Published: June 2006

AbstractPartial specification of a prior distribution can be appealing to an analyst, but there is no conventional way to update a partial prior. In this paper, we show how a framework for Bayesian updating with data can be based on the Dirichlet(a) process. Within this framework, partial information predictors generalize standard minimax predictors and have interesting multiple‐point shrinkage properties. Approximations to partial‐information estimators for squared error loss are defined straightforwardly, and an estimate of the mean shrinks the sample mean. The proposed updating of the partial prior is a consequence of four natural requirements when the Dirichlet parameter a is continuous. Namely, the updated partial posterior should be calculable from knowledge of only the data and partial prior, it should be faithful to the full posterior distribution, it should assign positive probability to every observed event {X,}, and it should not assign probability to unobserved events not included in the partial prior specification.
Selecting a power‐series distribution for goodness of fit
Authors: Wani Jagannath K. , Lo Hing‐Po 
Published: June 2006

AbstractThe binomial, Poisson, logarithmic, negative binomial, and extended negative binomial distributions are characterized in the class of power‐series distributions (1) through a differential equation based on the ratio of two successive derivatives of the series function, (2) through the ratio of two probabilities associated with two successive values in the range of the random variable, and (3) through the ratio of two consecutive factorial moments. The ratios referred to in (2) and (3) above can be utilized to discriminate between the five power‐series distributions mentioned at the beginning.
Discrete approximations to the Csiszár, Renyi, and Fisher measures of information
Authors: Zografos K. , Ferentinos K. , Papaioannou T. 
Published: June 2006

AbstractThe problem of loss of information due to the discretization of data and its estimate is studied for various measures of information. The results of Ghurye and Johnson (1981) are generalized and supplemented for the Csiszár and Renyi measures of information as well as for Fisher's information matrix.
The geometry of case deletion and the assessment of influence in nonlinear regression
Authors: Ross William H. 
Published: June 2006

AbstractNumerous influence measures are available for use in linear regression. By contrast, very little has been done for nonlinear models. A notable exception is Chapter 4 of Cook and Weisberg (1982). The extension of measures based on case deletion from the linear to the nonlinear model usually involve linear approximation. In this paper, the geometry of case deletion is studied with a view to assessing the adequacy of linear approximation in the construction of influence measures for nonlinear regression. Of particular interest is the adequacy of the one‐step estimator for the jack‐knifed pseudoestimates of the unknown parameter vector.
Connectedness of PBIB designs
Authors: Baksalary Jerzy K. , Tabis Zenon 
Published: June 2006

AbstractA necessary and sufficient condition for the connectedness of an m‐associate‐class PBIB design is derived in a form, and using an approach, different from those in Ogawa, Ikeda, and Kageyama (1984) and Saha and Kageyama (1984). The applicability of this condition is shown in the context of group‐divisible m‐associate‐class PBIB designs.
Bootstrapping regression models with BLUS residuals
Authors: Grenier Michèle , Léger Christian 
Published: June 2006

AbstractTo bootstrap a regression problem, pairs of response and explanatory variables or residuals can be resam‐pled, according to whether we believe that the explanatory variables are random or fixed. In the latter case, different residuals have been proposed in the literature, including the ordinary residuals (Efron 1979), standardized residuals (Bickel & Freedman 1983) and Studentized residuals (Weber 1984). Freedman (1981) has shown that the bootstrap from ordinary residuals is asymptotically valid when the number of cases increases and the number of variables is fixed. Bickel & Freedman (1983) have shown the asymptotic validity for ordinary residuals when the number of variables and the number of cases both increase, provided that the ratio of the two converges to zero at an appropriate rate. In this paper, the authors introduce the use of BLUS (Best Linear Unbiased with Scalar covariance matrix) residuals in bootstrapping regression models. The main advantage of the BLUS residuals, introduced in Theil (1965), is that they are uncorrelated. The main disadvantage is that only n —p residuals can be computed for a regression problem with n cases and p variables. The asymptotic results of Freedman (1981) and Bickel & Freedman (1983) for the ordinary (and standardized) residuals are generalized to the BLUS residuals. A small simulation study shows that even though only n — p residuals are available, in small samples bootstrapping BLUS residuals can be as good as, and sometimes better than, bootstrapping from standardized or Studentized residuals.
Seasonal adjustment in the eighties: Some problems and solutions
Authors: Dagum Estela Bee , Huot Guy , Morry Marietta 
Published: June 2006

AbstractStatistics Canada, like most statistical bureaus, is concerned with problems affecting the accuracy, the consistency, and the usefulness of seasonally adjusted series. The most serious problems affecting the accuracy of seasonally adjusted data in the eighties are related to changes in trading‐day variations caused by changes in consumers' patterns and to the effect of the early arrival of Easter in March (1986) and the beginning of April (1980, 1983, 1985, 1988). The problems affecting consistency mainly result from the lack of uniform practices for the seasonal adjustment of related series and economic aggregates. This lack of uniformity is present in (1) the seasonal adjustment of current observations, which can be done by applying the X‐11‐ARIMA program in four different modes; and (2) the seasonal adjustment of key economic and social indicators, which are aggregates and give different results if adjusted directly or indirectly (through the aggregation of each seasonally adjusted component). Finally, the problem of usefulness of seasonally adjusted data manifests itself for series that are largely irregular, posing then the need for further smoothing.
A look at response errors in the labour force survey
Authors: Lemaitre Georges 
Published: June 2006

AbstractIn conducting surveys, survey‐takers impose upon respondents certain cognitive and perceptual tasks the difficulty of which will depend upon a variety of factors. This paper examines the types of questions asked in the Canadian Labour Force Survey with an eye to assessing their “difficulty” and to identifying covariates of difficulty, with respect to both the nature of the information sought and the circumstances of the reinterview. The conclusions are extended to retrospective surveys, where response errors often lead to estimates that are seriously biased.
Parameter estimation under orthant restrictions
Authors: Fernández Miguel A. , Rueda Cristina , Salvador Bonifacio 
Published: June 2006

AbstractThe authors consider the estimation of linear functions of a multivariate parameter under orthant restrictions. These restrictions are considered both for location models and for the Poisson distribution. For these models, situations are characterized for which the restricted maximum likelihood estimator dominates the unrestricted one for the estimation of any linear function of the parameter. The results obtained point directly to the importance of the dimension of the parameter space, the central direction of the cone and its vertex in these cases. Special attention is given to examples, such as the one‐way analysis of variance, where the estimation of individual interesting linear functions of the parameter, as the coordinates and the differences between them, is also treated.
On Hacking's fiducial theory of inference
Authors: Sharma Shyam S. 
Published: June 2006

AbstractFisher's theory of fiducial inference is known to lead to mathematical inconsistencies. Hacking (1965) puts forward a new basis for fiducial inference. In this paper we have presented Hacking's theory retaining his original terminology but replacing his notation by more usual mathematical notation. His condition of irrelevance is derived in an explicit mathematical form, making it more comprehensible to statisticians. Further an example is constructed to show that Hacking's theory also leads to mathematical inconsistencies.
Deficiencies of minimum discrepancy estimators
Authors: Ponnapalli R. 
Published: June 2006

AbstractSuppose the multinomial parameterspr(θ) are functions of a real valued parameter 0,r= 1,2, …,k.A minimum discrepancy (m.d.) estimator θ of θ is defined as one which minimises the discrepancy functionD= Σnrf(pr/nr), for a suitable functionfwherenris the relative frequency inr‐th cell,r=1,2, …, k.All the usual estimators like maximum likelihood (m. l), minimum chi‐square (m. c. s.)., etc. arem.d.estimators. Allm.d.estimators have the same asymptotic (first order) efficiency. They are compared on the basis of their deficiencies, a concept recently introduced by Hodges and Lehmann [2]. The expression for least deficiency at any θ is derived. It is shown that in general uniformly least deficient estimators do not exist. Necessary and sufficient conditions onpr(0) form. t.andm. c. s.estimators to be uniformly least deficient are obtained.
The design of a clinical trial when there are two categories of patients
Authors: Donner Allan 
Published: June 2006

AbstractStrategies are investigated for selecting one of two medical treatments when patients may be stratified into two distinct categories on the basis of their expected difference in response to the two treatments. The relative effectiveness of the following three strategies are assessed: (1) separate decisions made independently for the two categories, (2) a single overall decision made on the basis of simple pooling, and (3) the Bayes strategy.
Bayes two‐decision procedures for two‐sample problems and rank‐order data
Authors: Baskerville J. C. , Solomon D. L. 
Published: June 2006

AbstractA two‐sample problem for rank‐order data is formulated as a two‐decision problem. Using the general Bayes solution, Bayes procedures are derived for several configurations of the set of states of nature including some for which the problem is distribution‐free. It is shown that for certain prior distributions these procedures reduce to classical LMP rank tests. Some devices for selection of prior distributions are suggested. It is shown that the Bayes risk of these procedures tends to zero as sample sizes increase.
Autoregressive moving‐average convolution processes on the unit circle
Authors: Zwiers F. W. 
Published: June 2006

AbstractARMA convolution models for processes in continuous space (in this case the unit circle) and discrete time are derived as a natural extension of the usual Box‐Jenkins models. Both weakly time‐stationary and nonstationary processes are considered. Sufficient conditions for the existence of weakly time‐stationary ARcMAc processes are derived, and the covariance functions for some processes are computed. It is demonstrated that the usual scalar and multivariate ARMA processes can be embedded within the larger class of ARCMAc models. A possible application of these models to sea‐surface temperature prediction is discussed.
A class of time‐reversible semi‐Markov processes
Authors: Schaufele Ronald A. 
Published: June 2006

AbstractIn this paper, we investigate a class of semi‐Markov processes, first touched upon lightly in Pyke and Schaufele (1966), that are time‐reversible. Results that are difficult to prove for semi‐Markov processes in general are often made more simple for time‐reversible semi‐Markov processes, and some examples are given.
Asymptotic spacings theory with applications to the two‐sample problem
Authors: Holst Lars , Rao J. S. 
Published: June 2006

AbstractThe asymptotic distribution theory of test statistics which are functions of spacings is studied here. Distribution theory under appropriate close alternatives is also derived and used to find the locally most powerful spacing tests. For the two‐sample problem, which is to test if two independent samples are from the same population, test statistics which are based on “spacing‐frequencies” (i.e., the numbers of observations of one sample which fall in between the spacings made by the other sample) are utilized. The general asymptotic distribution theory of such statistics is studied both under the null hypothesis and under a sequence of close alternatives.
Testing retrospective hypotheses
Authors: Maymin Zakhar , Gutmann Sam 
Published: June 2006

AbstractThis paper develops a conditional approach to testing hypotheses set up after viewing the data. For example, suppose Xi are estimates of location parameters θi, i = 1,…n. We show how to compute p‐values for testing whether θ1 is one of the three largest θi after observing that X1 is one of the three largest Xi, or for testing whether θ1 > θ2 > … > θn after observing X1 >X2> … >Xn.