Author: Federica GiummolèPublisher:
ISBN:
Category :
Languages : en
Pages : 12
Book Description
Improved Maximum Likelihood Estimation in Heteroscedastic Nonlinear Regression Models
Author: Federica GiummolèCorrected Maximum Likelihood Estimation in a Class Os Symmetric Nonlinear Regression Models
Author: Gauss Moutinho CordeiroPublisher:
ISBN:
Category :
Languages : en
Pages : 14
Book Description
Semiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and Monte Carlo Evidence
Author: Jian YangPublisher: London : Department of Economics, University of Western Ontario
ISBN:
Category : Mathematics
Languages : en
Pages : 68
Book Description
Maximum Likelihood Estimation of Misspecified Models
Author: T. FombyPublisher: Elsevier
ISBN: 9780762310753
Category : Business & Economics
Languages : en
Pages : 280
Book Description
Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.
Maximum Likelihood Estimation
Author: Scott R. EliasonPublisher: SAGE Publications, Incorporated
ISBN:
Category : Mathematics
Languages : en
Pages : 100
Book Description
This is a short introduction to Maximum Likelihood (ML) Estimation. It provides a general modeling framework that utilizes the tools of ML methods to outline a flexible modeling strategy that accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models linking endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, the author discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Maximum Likelihood Estimation and Large-sample Inference for Generalized Linear and Nonlinear Regression Models
Author: Bent JøgensenSemiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and GARCH Models
Author: Selected Proceedings of the Symposium on Inference for Stochastic Processes
Author: Ishwar V. BasawaPublisher: IMS
ISBN: 9780940600515
Category : Mathematics
Languages : en
Pages : 370
Book Description
Consistent Maximum Likelihood Estimation of the Nonlinear Regression Model with Normal Errors
Author: Risto D. H. HeijmansPublisher:
ISBN:
Category : Economics
Languages : en
Pages : 26
Book Description
Author: R. D. H. Heijmans