Recurrence relations for moments of different orders of extremes from gamma distribution

Certain recurrence relations for the moments of different orders of the largest order statistic from a gamma distribution with shape parameter p are obtained. By using this it is shown that for obtaining the moment of any order of each order statistic of a sample of size n from the gamma distribution, one has to evaluate at most n-2 single integrals.     

Optimal 2n-p fractional factorial designs for dispersion effects under a location-diapersion model

We consider main effects models for 2-level experiments that also include. Parameters characterizing potential dispersion effects due to specified factors. One special case is considered. In this case only a single specified factor is responsible for the dispersion effects. We determine the connection between alias relations and Optimality of a design for estimation of dispersion effects in the class of regu!ar fractional Y - P factorial designs of resolution III or higher. This rmectioil heips US identify those designs that are A-optimal for estimating dispersion effects by a suitable choice of defining contrasts. in particuiar, we show that an increase in efficiency with respect to dispersion effects is accompanied by a loss iii efficiency for estimating the location effects. In practice, one mmt thcrcfcre accept a trade& between the efficiencies associated with estirnates of location effects and dispersion effects.     

The influence in comparing covariance matrices

The influence measure for the likelihood ratio test for comparing two covariance matrices is derived using the influence curve approach under the normality assumption. The influence measure for testing the equality of covariance matrices against the arbitrariness of them is partitioned into three influence measures: one for testing the equality of covariance matrices against the proportionality of them, another for testing the proportionality against the equality of correlations between them and the other for testing the equality of correlations against the arbitrariness. This partition implies that an observation can be influential in performing some tests among the four tests but not in performing the remaining tests. Thus the partition is more informative than considering the influence measure for the test of equality alone. Each influence measure is useful for detecting outliers in performing the corresponding likelihood ratio test.     

Facing Faculty Fears about Embracing the Ebook: Communication Strategies for Liaison Librarians

Carol Cramer and Ellen Daugman of Wake Forest University discussed faculty attitudes toward ebooks in the library collection. Cramer and Daugman shared communication strategies based on their experience balancing the print book preferences of some faculty with the budgetary and collection development needs of the library.     

最低工资标准与和谐劳动关系的构建——广州、佛山、深圳最低工资标准比较研究

最低工资保障问题是构建和谐劳动关系的核心内容和难点问题。对广州、佛山和深圳最低工资标准现状进行分析,并运用ELES模型测算其最低工资标准,测算结果显示：目前三市最低工资实际标准与理论标准仍有差距,其中广州的差距最小,佛山次之,深圳的差距最大;最低工资标准与职工平均工资比例偏低,与人均GDP比例关系失调,深圳最低工资执行标准总体优于广州和佛山。鉴此,提出应以发展线水平为目标制定最低工资标准等建议。     

Testing independence of several groups of variables

The null distribution of Wilks' likelihood-ratio criterion for testing independence of several groups of variables in a multivariate normal population is derived. Percentage points are tabulated for various values of the sample sizeN and partitions of p, the number of variables. This paper extends Mathai and Katiya's (1979) “sphericity” results and tables.     

Learning Concepts and Taxonomic Relations by Metric Learning for Regression

Ontology learning has become a major area of research within the current ontology engineering. The acquisition of concepts and taxonomic relations is one of the key issues of ontology learning. There are various taxonomic ways for the same domain and the related concepts. However, current ontology learning tools have not considered how to generate the most suitable taxonomy for the specific application. In this article, we present a new supervised approach for taxonomic relationship learning. Taking the Chinese unstructured text on the Web as the corpus and a certain particular domain application as the guide, this method uses a given branch of the target ontology and integrates multi-strategy which includes shallow syntactic analysis and kinds of statistical measures to extract concepts and to determine the concepts’ hierarchy numbers and is-a relations. The experiments using a working prototype of the system revealed the improved performance of domain ontology taxonomic relations learning.     

On some study of skew-t distributions

Abstract

In this note, through ratio of independent random variables, new families of univariate and bivariate skew-t distributions are introduced. Probability density function for each skew-t distribution will be given. We also derive explicit forms of moments of the univariate skew-t distribution and recurrence relations for its cumulative distribution function. Finally we illustrate the flexibility of this class of distributions with applications to a simulated data and the volcanos heights data.     

Functionals of Markovian Branching D-BMAPS

Abstract

We consider a stochastic system in which Markovian customer attribute processes are initiated at customer arrivals in a discrete batch Markovian arrival process (D-BMAP). We call the aggregate a Markovian branching D-BMAP. Each customer attribute process is an absorbing discrete time Markov chain whose parameters depend both on the phase transition, of the driving D-BMAP, and the number of arrivals taking place at the customer's arrival instant. We investigate functionals of Markovian branching D-BMAPs that may be interpreted as cumulative rewards collected over time for the various customers that arrive to the system, in the transient and asymptotic cases. This is achieved through the derivation of recurrence relations for expected values and Laplace transforms in the former case, and Little's law in the latter case.     

Computing the moments of order statistics from nonidentical random variables

In this paper, we establish new representations, identities and recurrence relations of order statistics (o.s.) arising from general independent nonidentically distributed random variables (r.v.s). These recurrence relations will enable one to compute all moments of all o.s. in a simple manner. Applications for some known distributions are given.     

Proportional reversed hazard rate model and its applications

The purpose of this paper is to study the structure and properties of the proportional reversed hazard rate model (PRHRM) in contrast to the celebrated proportional hazard model (PHM). The monotonicity of the hazard rate and the reversed hazard rate of the model is investigated. Some criteria of aging are presented and the inheritance of the aging notions (of the base distribution) by the PRHRM is studied. Characterizations of the model involving Fisher information are presented and the statistical inference of the parameters is discussed. Finally, it is shown that several members of the proportional reversed hazard rate class have been found to be useful and flexible in real data analysis.     

Maximum likelihood estimation for the generalized poisson distribution

The generalized Poisson distribution;containing two

parameters and studied by many researchers; describes the distribution of busy periods under a queueing system and has very interesting properties; The probabilities for successive classes depend upon the previous occurrences; The problem of admissible maximum likelihood estimators for for the parameters Is discussed and a necessary and sufficient condition is derived for which unique admissible maximum likelihood estimators exist; The first; order terms in the biases; variances and the covariance of these maximum likelihood estimators are obtained.     

Extended exponential distribution based on order statistics

The extended exponential distribution due to Nadarajah and Haghighi (2011 Nadarajah, S., Haghighi, F. (2011). An extension of the exponential distribution. Statistics 45:543–558.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) is an alternative to and always provides better fits than the gamma, Weibull, and the exponentiated exponential distributions whenever the data contain zero values. We establish recurrence relations for the single and product moments of order statistics from the extended exponential distribution. These recurrence relations enable computation of the means, variances, and covariances of all order statistics for all sample sizes in a simple and efficient manner. By using these relations, we tabulate the means, variances, and covariances of order statistics and derive best linear unbiased estimates of the extended exponential distribution. Finally, a data application is provided.     

The Generalized Pascal Triangle and the Matrix Variate Jensen-Logistic Distribution

This article defines the so called Generalized Matrix Variate Jensen-Logistic distribution. The relevant applications of this class of distributions in Configuration Shape Theory consist of a more efficient computation, supported by the corresponding inference. This demands the solution of two important problems: (1) the development of analytical and efficient formulae for their k-th derivatives and (2) the use of the derivatives to transform the configuration density into a polynomial density under some special matrix Kummer relation, indexed in this case by the Jensen-Logistic kernel. In this article, we solve these problems by deriving a simple formula for the k-th derivative of the density function, avoiding the usual partition theory framework and using a generalization of Pascal triangles. Then we apply the results by obtaining the associated Jensen-Logistic Kummer relations and the configuration polynomial density in the setting of Statistical Shape Theory.     

A SEMIPARAMETRIC BAYESIAN APPROACH TO NETWORK MODELLING USING DIRICHLET PROCESS PRIOR DISTRIBUTIONS

This paper considers the use of Dirichlet process prior distributions in the statistical analysis of network data. Dirichlet process prior distributions have the advantages of avoiding the parametric specifications for distributions, which are rarely known, and of facilitating a clustering effect, which is often applicable to network nodes. The approach is highlighted for two network models and is conveniently implemented using WinBUGS software.     

A General Recurrence Relation for the Moments of Bivariate and Trivariate Order Statistics

In this article, by using the dropping argument, a general recurrence relation satisfied by the joint cumulative distribution functions of order statistics from any arbitrary bivariate distribution function is established. This recurrence relation is the first bivariate version of the basic triangle rule for order statistics arisen from univariate distribution function. Finally, this relation is extended to the trivariate case. These lead to similar identities for product moments (of any order) of order statistics.     

Recurrence relations for single and product moments of record values from generalized pareto distribution

In this paper we establish some recurrence relations satisfied by single and product moments of upper record values from the generalized Pareto distribution. It is shown that these relations may be used to obtain all the single and product moments of all record values in a simple recursive manner. We also show that similar results established recently by Balakrishnan and Ahsanullah (1993) for the upper record values from the exponential distribution may be deduced by letting the shape parameter p tend to 0.