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Simulated Maximum Likelihood, Pseudo‐Maximum Likelihood, and Nonlinear Least Squares Methods

Christian Gouriéroux and Alain Monfort

in Simulation-based Econometric Methods

Published in print:
1997
Published Online:
November 2003
ISBN:
9780198774754
eISBN:
9780191596339
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/0198774753.003.0003
Subject:
Economics and Finance, Econometrics

The simulated analogues to Maximum Likelihood, Pseudo‐Maximum Likelihood, and Non‐Linear Least Squares Methods are presented. Their asymptotic properties and bias corrections are given under various ... More


Time Series Analysis by State Space Methods: Second Edition

James Durbin and Siem Jan Koopman

Published in print:
2012
Published Online:
December 2013
ISBN:
9780199641178
eISBN:
9780191774881
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199641178.001.0001
Subject:
Mathematics, Probability / Statistics

This book presents a comprehensive treatment of the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as ... More


Bayesian estimation of parameters

J. Durbin and S.J. Koopman

in Time Series Analysis by State Space Methods: Second Edition

Published in print:
2012
Published Online:
December 2013
ISBN:
9780199641178
eISBN:
9780191774881
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199641178.003.0013
Subject:
Mathematics, Probability / Statistics

This chapter discusses the use of importance sampling for the estimation of parameters in Bayesian analysis for models of Part I and Part II. It first develops the analysis of the linear Gaussian ... More


Bayesian theory

Ziheng Yang

in Molecular Evolution: A Statistical Approach

Published in print:
2014
Published Online:
August 2014
ISBN:
9780199602605
eISBN:
9780191782251
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199602605.003.0006
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Evolutionary Biology / Genetics

This chapter summarizes the Frequentist–Bayesian controversy in statistics, and introduces the basic theory of Bayesian statistical inference, such as the prior, posterior, and Bayes’ theorem. ... More


Finite Mixture Models

Russell Cheng

in Non-Standard Parametric Statistical Inference

Published in print:
2017
Published Online:
September 2017
ISBN:
9780198505044
eISBN:
9780191746390
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198505044.003.0017
Subject:
Mathematics, Probability / Statistics

Fitting a finite mixture model when the number of components, k, is unknown can be carried out using the maximum likelihood (ML) method though it is non-standard. Two well-known Bayesian Markov chain ... More


Monte Carlo methods

Joseph F. Boudreau and Eric S. Swanson

in Applied Computational Physics

Published in print:
2017
Published Online:
February 2018
ISBN:
9780198708636
eISBN:
9780191858598
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198708636.003.0007
Subject:
Physics, Theoretical, Computational, and Statistical Physics

Monte Carlo methods are those designed to obtain numerical answers with the use of random numbers . This chapter discusses random engines, which provide a pseudo-random pattern of bits, and their use ... More


Monte Carlo methods

Michael P. Allen and Dominic J. Tildesley

in Computer Simulation of Liquids: Second Edition

Published in print:
2017
Published Online:
November 2017
ISBN:
9780198803195
eISBN:
9780191841439
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198803195.003.0004
Subject:
Physics, Theoretical, Computational, and Statistical Physics, Soft Matter / Biological Physics

The estimation of integrals by Monte Carlo sampling is introduced through a simple example. The chapter then explains importance sampling, and the use of the Metropolis and Barker forms of the ... More


Ensembles with hard constraints

A.C.C. Coolen, A. Annibale, and E.S. Roberts

in Generating Random Networks and Graphs

Published in print:
2017
Published Online:
May 2017
ISBN:
9780198709893
eISBN:
9780191780172
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198709893.003.0005
Subject:
Physics, Theoretical, Computational, and Statistical Physics

This chapter introduces random graph ensembles involving hard constraints such as setting a fixed total number of links or fixed degree sequence, including properties of the partition function. It ... More


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