We describe a multivariate, multilevel, pseudo maximum likelihood estimation method for multistage stratified cluster sampling designs, including finite population and unequal probability sampling. Multilevel models can be estimated with this method while incorporating the sampling design in the standard error computation. Design based adjustment of the likelihood ratio test (LRT) statistic is ...

Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduction to a propositional formula in DNF. Calculating the probability of such a formula involves the disjoint-sum-problem, which is computationally hard. In this work we introduce a new approximation method for ProbLog inference which exploits the DNF to focus samp...

We describe an extension of the pseudo maximum likelihood (PML) estimation method developed by Skinner (1989) to multistage strati ̄ed cluster sampling designs, including ̄nite population and unequal probability sampling. We conduct simulation studies to evaluate the performance of the proposed estimator. The estimator is also compared to the general estimating equation (GEE) method for linear r...

This paper deals with estimation of probabilities of rare events in static simulation models using a fast adaptive two-stage procedure based on importance sampling and Kullback-Liebler’s cross-entropy (CE). More specifically, at the first stage we estimate the optimal parameter vector in the importance sampling distribution using CE, and at the second stage we estimate the desired rare event pr...

In Hill [11], it was shown that an almost-sure theory for a Fraïssé class K relative to an asymptotic probability measure with “independent sampling” is necessarily super-simple of finite rank with D(x=x) = 1. In this note, we show that this independent sampling hypothesis is much stronger than necessary. By examining the Aldous-Hoover-Kallenberg (AHK) presentation of an asymptotic probability ...

Low-rank matrix completion (LRMC) problems arise in a wide variety of applications. Previous theory mainly provides conditions for completion under missing-at-random samplings. This paper studies deterministic conditions for completion. An incomplete d ×N matrix is finitely rank-r completable if there are at most finitely many rank-r matrices that agree with all its observed entries. Finite com...

To find the relationship of different variables, training, compensation, feedback, and job involvement on productivity of employees in electric supply company in Pakistan. The aim of this research is to find out the impact of variables on employee productivity. The researcher is use the quantitative approach of research. The population for this research are the employees of electricity supply c...

Most aircraft fleets nowadays are operating under the concept of damage tolerance, which requires an aircraft to have sufficient residual strength in the presence of damage in one of its principal structural elements (PSE) during the interval of service inspections. The residual strength however is significantly reduced due to multi site damage (MSD). In the present paper, a probabilistic frame...

The area of large deviations is a set of asymptotic results on rare events probabilities and a set of methods to derive such results. Large deviations theory is a very active field in applied probability, and finds important applications in finance, where questions related to extremal events play an increasingly major role. Financial applications are various, and range from Monte-Carlo methods ...

Asymptotic approximations and importance sampling methods are presented for evaluating a class of probability integrals with multiple design points that may arise in the calculation of the reliability of uncertain dynamical systems. An approximation based on asymptotics is used as a ®rst step to provide a computationally ecient estimate of the probability integral. The importance sampling meth...