Information theoretic estimators for the first-order spatial autoregressive model are introduced, small sample properties are investigated, and the estimator is applied empirically. Monte Carlo experiments are used to compare finite sample performance of more traditional spatial estimators to three different information theoretic estimators, including maximum empirical likelihood, maximum empir...

This article has investigated the asymptotic distribution of the maximum likelihood estimator in a stochastic frontier function when the firms are all technically efficient. For such a situation, the true parameter vector is on the boundary of the parameter space, and the scores are linearly dependent. The maximum likelihood estimator is shown to be a mixture of certain truncated distributions....

This paper will study the estimation of parameter of Topp-Leone distribution based on lower record values. First, the minimum variance unbiased estimator and maximum likelihood estimator are obtained. Then the Bayes estimator is derived under symmetric loss function and further the empirical Bayes estimators is also obtained based on marginal probability density of record sample and maximum lik...

Geographically Weighted Regression (GWR) is the development of multiple linear regression models used in spatial data. The assumption heterogeneity results each location having different characteristics and allows relationships between response variable predictor to be unknown, hence nonparametric becomes one alternatives that can used. In addition, functions are not always same variables. This...

Measurements made by several laboratories may exhibit non-negligible between-laboratory variability, as well as diierent within-laboratory variances. Also, the number of measurements made at each laboratory often diier. A question of fundamental importance in the analysis of such data is how to form a best consensus mean, and what uncertainty to attach to this estimate. An estimation equation a...

The estimation of the parameters of Burr type III distribution based on dual generalized order statistics is considered by using the maximum likelihood (ML) approach as well as the Bayesian approach. The exact expression of the expected Fisher information matrix of the parameters in the distribution is obtained. Also, an approximation based on Lindley is used to obtain the Bayes estimator. To c...