An overview of composite likelihood methods
A survey of recent developments in the theory and application of composite likelihood is
provided, building on the review paper of Varin (2008). A range of application areas …
provided, building on the review paper of Varin (2008). A range of application areas …
[图书][B] Analysis of ordinal categorical data
A Agresti - 2010 - books.google.com
Statistical science's first coordinated manual of methods for analyzing ordered categorical
data, now fully revised and updated, continues to present applications and case studies in …
data, now fully revised and updated, continues to present applications and case studies in …
On composite marginal likelihoods
C Varin - Asta advances in statistical analysis, 2008 - Springer
Composite marginal likelihoods are pseudolikelihoods constructed by compounding
marginal densities. In several applications, they are convenient surrogates for the ordinary …
marginal densities. In several applications, they are convenient surrogates for the ordinary …
The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models
CR Bhat - Transportation Research Part B: Methodological, 2011 - Elsevier
The likelihood functions of multinomial probit (MNP)-based choice models entail the
evaluation of analytically-intractable integrals. As a result, such models are usually …
evaluation of analytically-intractable integrals. As a result, such models are usually …
[HTML][HTML] On weighting of bivariate margins in pairwise likelihood
Composite and pairwise likelihood methods have recently been increasingly used. For
clustered data with varying cluster sizes, we study asymptotic relative efficiencies for various …
clustered data with varying cluster sizes, we study asymptotic relative efficiencies for various …
A flexible spatially dependent discrete choice model: formulation and application to teenagers' weekday recreational activity participation
This study proposes a simple and practical Composite Marginal Likelihood (CML) inference
approach to estimate ordered-response discrete choice models with flexible copula-based …
approach to estimate ordered-response discrete choice models with flexible copula-based …
A comparison of the maximum simulated likelihood and composite marginal likelihood estimation approaches in the context of the multivariate ordered-response …
This chapter compares the performance of the maximum simulated likelihood (MSL)
approach with the composite marginal likelihood (CML) approach in multivariate ordered …
approach with the composite marginal likelihood (CML) approach in multivariate ordered …
Pairwise likelihood inference for general state space models
This article concerns parameter estimation for general state space models, following a
frequentist likelihood-based approach. Since exact methods for computing and maximizing …
frequentist likelihood-based approach. Since exact methods for computing and maximizing …
Data integration with high dimensionality
X Gao, RJ Carroll - Biometrika, 2017 - academic.oup.com
We consider situations where the data consist of a number of responses for each individual,
which may include a mix of discrete and continuous variables. The data also include a class …
which may include a mix of discrete and continuous variables. The data also include a class …
The composite marginal likelihood (CML) inference approach with applications to discrete and mixed dependent variable models
CR Bhat - Foundations and Trends® in Econometrics, 2014 - nowpublishers.com
This monograph presents the basics of the composite marginal likelihood (CML) inference
approach, discussing the asymptotic properties of the CML estimator and the advantages …
approach, discussing the asymptotic properties of the CML estimator and the advantages …