This paper analyses the properties of standard estimators, tests, and con…dence sets (CS’s) in a class of models in which the parameters are unidenti…ed or weakly identi…ed in some parts of the parameter space. The paper also introduces a method to make the tests and CS’s robust to such identi…cation problems. The results apply to a class of extremum estimators and corresponding tests and CS’s,...

In this paper we introduce the Extended Method of Moments (XMM) estimator. This estimator accommodates a more general set of moment restrictions than the standard Generalized Method of Moments (GMM) estimator. More specifically, the XMM differs from the GMM in that it can handle not only uniform conditional moment restrictions (i.e. valid for any value of the conditioning variable), but also lo...

This article analyzes generalized method of moments estimation when the sample is not a random draw from the population of interest. Auxiliary information, in the form of moments from the population of interest, is exploited to compute weights that are proportional to the inverse probability of selection. The essential idea is to construct weights for each observation in the primary data such t...

Exact expressions for single and product moments of generalized order statistics are derived when the underlying population is assumed to have a Rayleigh distribution. Bayesian estimators and highest posterior density (HPD) credible intervals are obtained for the scale parameter and reliability function based on generalized order statistics. We also derive the Bayes predictive estimator and HPD...

Tthe Zografos–Balakrishnan-log-logistic (ZBLL) distribution is a new distribution of three parameters that has been introduced by Ramos et el. [1], and They presented some properties of the new distribution such as its probability density function, The cumulative distribution function, The  moment generating function, its hazard (failure) rate function, quantiles and moments, Rényi and Shannon ...

This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in the paper, the (quasi) maximum likelihood estimator may not be computationally feasible in ma...

This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in this paper, the (quasi) maximum likelihood estimator may not be computationally feasible in m...