The EGARCH is a popular model for discrete time volatility since it allows for asymmetric effects and naturally ensures positivity even when including exogenous variables. Estimation and inference is usually done via maximum likelihood. Although some progress has been made recently, a complete distribution theory of MLE for EGARCH models is still missing. Furthermore, the estimation procedure i...

The ability to determine in real-time the geographic location of client nodes is an important tool in wireless networks, allowing instantaneous mobile tracking, implementation of location-aware services and also efficient channel and power allocation planning. Among existing classical cooperative localization techniques for wireless networks, the maximum likelihood estimator (MLE) is theoretica...

In this paper the classical estimators of the shape parameter for the Burr Type XII distribution, such as, the Maximum Likelihood Estimator (MLE), the Uniformly Minimum Variance Unbiased Estimator (UMVUE), and the Minimum Mean Squared Error (MinMSE) estimator are obtained. Then the problem of finding the minimax estimators of this parameter under the squared log error, precautionary, and weight...

This paper presents a speech-model using the Linear Predictive (LP) residual signal and Maximum Likelihood Estimator (MLE). With this model an accuracy of the reverberation time estimation can be improved. During past decade, the reverberation time estimation was performed using only maximum likelihood detector, which resulted in excess time of estimation. For the purpose of estimating room aco...

The problem of estimating the number of members in a multicast session through probabilistic polling corresponds to that of estimating the parameter n of the Binomial n p , distribution. This allows an interval estimator for n to be derived. The tradeoff between the relative dispersion of this estimator and the overhead it requires is characterized in a manner that may be mapped to application ...

This paper proposes and implements a tractable approach to detect group structure in panel data. The mechanism works by means of a panel structure model, which assumes that individuals form a number of homogeneous groups in a heterogeneous population. Within each group, the (linear) regression coefficients are the same, while they may be different across different groups. The econometrician is ...

We consider some inference problems concerning the drift parameters vector of diffusion process. Namely, we consider the case where the parameters vector is suspected to satisfy certain restriction. Under such a design and imprecise prior information, we propose Stein-rule (or shrinkage) estimators which improves over the performance of the classical maximum likelihood estimator (MLE). By using...

A recent short communication [1] showed that an orthogonal subspace projection (OSP) classifier developed for hyperspectral image classification in [2] was equivalent to a maximum likelihood estimator (MLE) resulting from a standard method of linear unmixing. It further concluded that the MLE subsumed the OSP classifier in spite of a constant difference in their magnitudes. Coincidentally, the ...

In this article, we propose generalized two-parameter (GTP) estimators and an algorithm for the estimation of shrinkage parameters to combat multicollinearity in multinomial logit regression model. addition, mean squared error properties are derived. A simulation study is conducted investigate performance proposed different sample sizes, degrees multicollinearity, number explanatory variables. ...

This paper presents a speech-model using the Linear Predictive (LP) residual signal and Maximum Likelihood Estimator (MLE). With this model an accuracy of the reverberation time estimation can be improved. During past decade, the reverberation time estimation was performed using only maximum likelihood detector, which resulted in excess time of estimation. For the purpose of estimating room aco...