We describe a Monte Carlo method to approximate the maximum likelihood estimate (MLE), when there are missing data and the observed data likelihood is not available in closed form. This method uses simulated missing data that are independent and identically distributed and independent of the observed data. Our Monte Carlo approximation to the MLE is a consistent and asymptotically normal estima...

y In this paper, a space-alternating generalized expectation-maximization (SAGE) algorithm is presented for the numerical computation of maximum-likelihood (ML) and penalized maximum-likelihood (PML) estimates of the parameters of covariance matrices with linear structure for complex Gaussian processes. By using a less informative hidden-data space and a sequential parameter-update scheme, a SA...

This paper presents the statistical inference on the parameters of the Burr type III distribution, when the data are Type-II hybrid censored. The maximum likelihood estimators are developed for the unknown parameters using the EM algorithm method. We provided the observed Fisher information matrix using the missing information principle which is useful for constructing the asymptotic confidence...

In statistics, an expectationmaximization (EM) algorithm is an iterative method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. The EM iteration alternates between performing an expectation (E) step, which creates a function for the expectation of the log-likelihood evaluated usin...

The Expectation/Conditional Maximisation Either (ECME) algorithm has proven to be an effective way of accelerating the Expectation Maximisation (EM) algorithm for many problems. Recognising the limitation of using prefixed acceleration subspaces in ECME, we propose a Dynamic ECME (DECME) algorithm which allows the acceleration subspaces to be chosen dynamically. The simplest DECME implementatio...

genetic parameters and trends for milk and fat yields as well as for fat percentage were estimated from 35,438 milk production records (305d, 2x) of 17,971 holstein dairy cattle in 133 herds during the period of 1990-2003 in khorasan province. variance components were estimated using restricted maximum likelihood statistical method applying univariate and repeatability animal models. for the un...

We propose likelihood and restricted likelihood ratio tests for goodness-of-fit of nonlinear regression. The first order Taylor approximation around the MLE of the regression parameters is used to approximate the null hypothesis and the alternative is modeled nonparametrically using penalized splines. The exact finite sample distribution of the test statistics is obtained for the linear model a...

the objective of the present study was to estimate genetic parameters and genetic trends of growth traits , fleece weight and reproductive traits. data collected from 1993 to 2007 by the kermani breeding station were analyzed .traits were included birth weight (bw, n=2614), 3 months weight (3mw,n=2312), 6 months weight (6mw, n=1890), 9 months weight (9mw,n=1380) and 12 months weight (12mw,n=105...