Sparse State Recovery Versus Generalized Maximum-Likelihood Estimator of a Power System

Lecture 22: Maximum Likelihood Estimator

In the first part of this lecture, we will deal with the consistency and asymptotic distribution of maximum likelihood estimator. The second part of the lecture focuses on signal estimation/tracking. An estimator is said to be consistent if it converges to the quantity being estimated. This section speaks about the consistency of MLE and conditions under which MLE is consistent.

Maximum Likelihood Estimation of Parameters in Generalized Functional Linear Model

Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...

Consistency and Limiting Distribution of the Maximum Likelihood Estimator of a Generalized Threshold Model

The open-loop Threshold Model, proposed by Tong [30], is a piecewise-linear stochastic regression model useful for modeling conditionally normal response time-series data. However, in many applications, the response variable is conditionally non-normal, e.g. Poisson or binomially distributed. We generalize the open-loop Threshold Model by introducing the Generalized Threshold Model (GTM). Speci...

A simultaneous maximum likelihood estimator based on a generalized matched filter

Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression

Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zeroinflation occur. We study in this paper regression models based on the generalized Poisson distribution (Consul (1989)). These regression models which have been used for about 15 years do not belong to the class of generalized linear models considered by McCull...