Counts of a specific characteristic were obtained within regions defined on an object that was manufactured in proprietary setting. The count altered during production and resulted misaligned or overlapping data. A closed-formula maximum likelihood estimator (MLE) the new region means is derived using all available data independent Poisson model. MLE shown to be preferable estimators constructe...

This paper develops a simple and computationally efficient parametric approach to the estimation of general hidden Markov models (HMMs). For non-Gaussian HMMs, computation maximum likelihood estimator (MLE) involves high-dimensional integral that has no analytical solution can be difficult accurately. We develop new alternative method based on theory estimating functions deconvolution strategy....

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.

A transformational measurement model for structural equation modeling (SEM) of asymmetric non-normal data is proposed. This aligns with the expectation-maximization (EM) algorithm maximum likelihood estimation (MLE) method, creating adaptability to that deviate from normality. Distinctive properties connection and EM are maintenance normality assumption, which at core algorithm, applicability n...

The paper studies large sample asymptotic properties of the Maximum Likelihood Estimator (MLE) for the parameter of a continuous time Markov chain, observed in white noise. Using the method of weak convergence of likelihoods due to I.Ibragimov and R.Khasminskii [14], consistency, asymptotic normality and convergence of moments are established for MLE under certain strong ergodicity conditions o...

We review statistical methodology for estimating mean concentrations of potentially toxic pollutants in water, for small samples that are not normally distributed and often contain substantial numbers of nondetects, i.e. samples that are only known to be below some set of fixed thresholds. Maximum likelihood estimation (MLE) and regression on order statistics (ROS) are two main approaches that ...

How does the visual system combine information from different depth cues to estimate three-dimensional scene parameters? We tested a maximum-likelihood estimation (MLE) model of cue combination for perspective (texture) and binocular disparity cues to surface slant. By factoring the reliability of each cue into the combination process, MLE provides more reliable estimates of slant than would be...

We aimed to study the geographic variation in the incidence of COPD. We used health survey data (weighted to the population level) to identify 56,944 cases of COPD in Manitoba, Canada from 2001 to 2010. We used five cluster detection procedures, circular spatial scan statistic (CSS), flexible spatial scan statistic (FSS), Bayesian disease mapping (BYM), maximum likelihood estimation (MLE), and ...