A block composite likelihood is developed for estimation and prediction in large spatial datasets. The composite likelihood is constructed from the joint densities of pairs of adjacent spatial blocks. This allows large datasets to be split into many smaller datasets, each of which can be evaluated separately, and combined through a simple summation. Estimates for unknown parameters are obtained...

A block composite likelihood model is developed for estimation and prediction in large spatial datasets. The composite likelihood is constructed from the joint densities of pairs of adjacent spatial blocks. This allows large datasets to be split into many smaller datasets, each of which can be evaluated separately, and combined through a simple summation. Estimates for unknown parameters as wel...

Fisher analytically structured pivot functions (PFs) whose distribution does not suggested in 1930's depend on unknown parameters. These pivots provided a foundation for (asymptotic) statistical inference. Anderson (1958, p. 116) introduced the concept of a critical function of observables, which finds the rejection probability of a test for Fisher's pivot. Vinod (1998) shows that Godambe's (19...

ABSTRACT The aim of this study was to evaluate the status of information on forest and data transfer and to identify the gaps in information and data flow in forestry sector in Iran. The study evaluated the data and information flow in three levels (control offices level, provincial offices level and organizational offices level) using the document analysis and questioning (interviews and ques...

This very impressive paper brings together an enormous number of ideas from seemingly disconnected fields. There are frequentist ideas associated with estimating equations for general stochastic processes, and approaches to optimality associated with the names of Godambe and Heyde; connections with the method of maximum likelihood and the method of moments, also pseudo-likelihood, general Bayes...

An important problem in data analysis is how to choose an adequate family of distributions or statistical model to describe the values observed in any study. For this purpose the characterization theorems can be useful because, under general reasonable suppositions related to the nature of the experiment or the data, they allow us to reduce the possible set of distributions that can be used. On...

The paper proposes empirical Bayes (EB) estimators for simultaneous estimation of means in the natural exponential family (NEF) with quadratic variance functions (QVF) models. Morris (1982, 1983a) characterized the NEF-QVF distributions which include among others the binomial, Poisson and normal distributions. In addition to the EB estimators, we provide approximations to the MSE’s of t...

A culture conducive to information security practice is extremely important for organizations since information has to be critical assets in modern enterprises. Thus for understanding and improving the organizational behavior with regard to information security, enterprises may look into organizational culture and examine how it affects the effectiveness of implementing ISM. This study aims ...