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] Confidence, likelihood, probability
T Schweder, NL Hjort - 2016 - books.google.com
This lively book lays out a methodology of confidence distributions and puts them through
their paces. Among other merits they lead to optimal combinations of confidence from …
their paces. Among other merits they lead to optimal combinations of confidence from …
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 …
Space–time modelling of extreme events
R Huser, AC Davison - Journal of the Royal Statistical Society …, 2014 - academic.oup.com
Max-stable processes are the natural analogues of the generalized extreme value
distribution when modelling extreme events in space and time. Under suitable conditions …
distribution when modelling extreme events in space and time. Under suitable conditions …
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 …
High-order composite likelihood inference for max-stable distributions and processes
In multivariate or spatial extremes, inference for max-stable processes observed at a large
collection of points is a very challenging problem and current approaches typically rely on …
collection of points is a very challenging problem and current approaches typically rely on …
Issues and strategies in the selection of composite likelihoods
BG Lindsay, GY Yi, J Sun - Statistica Sinica, 2011 - JSTOR
The composite likelihood method has been proposed and systematically discussed by
Besag (1974), Lindsay (1988), and Cox and Reid (2004). This method has received …
Besag (1974), Lindsay (1988), and Cox and Reid (2004). This method has received …
Likelihood estimators for multivariate extremes
The main approach to inference for multivariate extremes consists in approximating the joint
upper tail of the observations by a parametric family arising in the limit for extreme events …
upper tail of the observations by a parametric family arising in the limit for extreme events …
Large-scale simulation of traffic flow using Markov model
Modeling and simulating movement of vehicles in established transportation infrastructures,
especially in large urban road networks is an important task. It helps in understanding and …
especially in large urban road networks is an important task. It helps in understanding and …
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 …