✦ LIBER ✦

Maximum-likelihood estimation for multivariate spatial linear coregionalization models

✍ Scribed by Hao Zhang

Publisher: John Wiley and Sons
Year: 2007
Tongue: English
Weight: 216 KB
Volume: 18
Category: Article
ISSN: 1180-4009
DOI: 10.1002/env.807

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Sparse Sampling and Maximum Likelihood E

Sparse Sampling and Maximum Likelihood Estimation for Boolean Models

✍ G. Ayala; J. R. Ferrandiz; F. Montes 📂 Article 📅 1991 🏛 John Wiley and Sons 🌐 English ⚖ 429 KB 👁 2 views

Variance estimation for multivariate dyn

Variance estimation for multivariate dynamic linear models

✍ Emanuel Barbosa; Jeff Harrison 📂 Article 📅 1992 🏛 John Wiley and Sons 🌐 English ⚖ 383 KB 👁 1 views

The problem of estimating unknown observational variances in multivariate dynamic linear models is considered. Conjugate procedures are possible for univariate models and also for special very restrictive common components models but they are not generally applicable. However, for clarity of operati

Covariance estimation for multivariate c

Covariance estimation for multivariate conditionally Gaussian dynamic linear models

✍ K. Triantafyllopoulos 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 245 KB 👁 1 views

## Abstract In multivariate time series, estimation of the covariance matrix of observation innovations plays an important role in forecasting as it enables computation of standardized forecast error vectors as well as the computation of confidence bounds of forecasts. We develop an online, non‐ite

Maximum Likelihood Estimation of Factor

Maximum Likelihood Estimation of Factor and Ideal Point Models for Paired Comparison Data

✍ Rung-Ching Tsai; Ulf Böckenholt 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 189 KB

Maximum likelihood linear regression for

Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models

✍ C.J. Leggetter; P.C. Woodland 📂 Article 📅 1995 🏛 Elsevier Science 🌐 English ⚖ 148 KB

A method of speaker adaptation for continuous density hidden Markov models (HMMs) is presented. An initial speaker-independent system is adapted to improve the modelling of a new speaker by updating the HMM parameters. Statistics are gathered from the available adaptation data and used to calculate

Maximum Likelihood Estimation and Infere

Maximum Likelihood Estimation and Inference (With Examples in R, SAS and ADMB) || Generalized Linear Models and Extensions

✍ Millar, Russell B. 📂 Article 📅 2011 🏛 John Wiley & Sons, Ltd 🌐 English ⚖ 747 KB

This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog