Author: Jeffrey E. Zabel
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 246
Book Description
The Likelihood Ratio Test as a Model Selection Criterion with an Application to Models of Female Labor Supply Behavior
Author: Jeffrey E. Zabel
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 246
Book Description
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 246
Book Description
The Likelihood Ratio Test as a Model Selection Criterion with an Application to Models of Female Labor Supply Behavior
Author: Jeffrey Edward Zabel
Publisher:
ISBN:
Category :
Languages : en
Pages : 107
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 107
Book Description
Dissertation Abstracts International
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 690
Book Description
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 690
Book Description
Maximum Likelihood Estimation of Models with Selection
Author: Dmitry Hindanov
Publisher:
ISBN:
Category : Child care
Languages : en
Pages : 150
Book Description
Publisher:
ISBN:
Category : Child care
Languages : en
Pages : 150
Book Description
American Doctoral Dissertations
Author:
Publisher:
ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 532
Book Description
Publisher:
ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 532
Book Description
Likelihood-ratio Test Statistic for the Finite-sample Case in Nonlinear Ordinary Differential Equation Models
Author: Christian Tönsing
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Abstract: Likelihood ratios are frequently utilized as basis for statistical tests, for model selection criteria and for assessing parameter and prediction uncertainties, e.g. using the profile likelihood. However, translating these likelihood ratios into p-values or confidence intervals requires the exact form of the test statistic's distribution. The lack of knowledge about this distribution for nonlinear ordinary differential equation (ODE) models requires an approximation which assumes the so-called asymptotic setting, i.e. a sufficiently large amount of data. Since the amount of data from quantitative molecular biology is typically limited in applications, this finite-sample case regularly occurs for mechanistic models of dynamical systems, e.g. biochemical reaction networks or infectious disease models. Thus, it is unclear whether the standard approach of using statistical thresholds derived for the asymptotic large-sample setting in realistic applications results in valid conclusions. In this study, empirical likelihood ratios for parameters from 19 published nonlinear ODE benchmark models are investigated using a resampling approach for the original data designs. Their distributions are compared to the asymptotic approximation and statistical thresholds are checked for conservativeness. It turns out, that corrections of the likelihood ratios in such finite-sample applications are required in order to avoid anti-conservative results
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Abstract: Likelihood ratios are frequently utilized as basis for statistical tests, for model selection criteria and for assessing parameter and prediction uncertainties, e.g. using the profile likelihood. However, translating these likelihood ratios into p-values or confidence intervals requires the exact form of the test statistic's distribution. The lack of knowledge about this distribution for nonlinear ordinary differential equation (ODE) models requires an approximation which assumes the so-called asymptotic setting, i.e. a sufficiently large amount of data. Since the amount of data from quantitative molecular biology is typically limited in applications, this finite-sample case regularly occurs for mechanistic models of dynamical systems, e.g. biochemical reaction networks or infectious disease models. Thus, it is unclear whether the standard approach of using statistical thresholds derived for the asymptotic large-sample setting in realistic applications results in valid conclusions. In this study, empirical likelihood ratios for parameters from 19 published nonlinear ODE benchmark models are investigated using a resampling approach for the original data designs. Their distributions are compared to the asymptotic approximation and statistical thresholds are checked for conservativeness. It turns out, that corrections of the likelihood ratios in such finite-sample applications are required in order to avoid anti-conservative results
Classification Error in Dynamic Discrete Choice Models: Implications for Female Labor Supply Behavior
Semiparametric Maximum Likelihood Estimation
Author: Mingchih Lee
Publisher:
ISBN:
Category : Labor supply
Languages : en
Pages : 200
Book Description
Publisher:
ISBN:
Category : Labor supply
Languages : en
Pages : 200
Book Description
Index to American Doctoral Dissertations
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 1252
Book Description
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 1252
Book Description
Maximum Likelihood Estimation with Sample Selection
Author: Boqing Wang
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 166
Book Description
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 166
Book Description