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17.953  Articles
1 of 1.796 pages  |  10  records  |  more records»
Maximum likelihood estimator is a suitable algorithm for passive target tracking applications. Nardone, Lindgren and Gong introduced this approach using batch processing. In this paper, the batch processing is converted into sequential processing for real... see more

This paper is concerned with the modifications of maximum likelihood, moments and percentile estimators of the two parameter Power function distribution. Sampling behavior of the estimators is indicated by Monte Carlo simulation. For some combinations of ... see more

We study n independent stochastic processes(xi (t),tiЄ[o,t1 ],i=1,......n) defined by a stochastic differential equation with diffusion coefficients depending nonlinearly on a random variables  and  (the random effects).The distributi... see more

We illustrate with examples when and how maximum likelihood estimators continue to be asymptotically efficient even under misspecified models. Also, we provide a necessary and sufficient condition under which a subset of the vector of MLE's retains its as... see more

Estimating the boost-phase trajectory of a ballistic missile using line of sight measurements from space-borne passive sensors is an important issue in missile defense. A well-known difficulty of this issue is the poor-observability of the target motion. ... see more

The Beta-Skew-t-EGARCH model was recently proposed in literature to model the volatility of financial returns. The inferences over the parameters of the model are based on maximum likelihood method. These estimators have good asymptotic properties, howev... see more

Burr type III is an important distribution used to model the failure time data. The paper addresses the problem of estimation of parameters of the Burr type III distribution based on maximum likelihood estimation (MLE) when the samples are left ... see more

A good  estimator has to fulfill some propertries such as unbiased, efficient and consistent. This research aims to study consistency and asymptotic normality of maximum likelihood estimator in MARS binary response model of Friedman, for predicting t... see more

In this paper, we discuss probit model on multivariate binary response. We assume that each of n individuals is observed in T responses. Yit is tth response on ith individual/subject and each response is binary. Each subject has covariate Xi (individual c... see more

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