latentUpdateBifactor

Conditional expectation proxies for bi-factor copula models
with linking copulas in different copula families

Inference methods for factor copula models for continuous data in Krupskii and Joe (2013) <doi:10.1016/j.jmva.2013.05.001>, Krupskii and Joe (2015) <doi:10.1016/j.jmva.2014.11.002>, Fan and Joe (2024) <doi:10.1016/j.jmva.2023.105263>, one factor truncated vine models in Joe (2018) <doi:10.1002/cjs.11481>, and Gaussian oblique factor models. Functions for computing tail-weighted dependence measures in Lee, Joe and Krupskii (2018) <doi:10.1080/10485252.2017.1407414> and estimating tail dependence parameter.

Pavel Krupskii

FactorCopulaModel

Factor Copula Models

Harry Joe

Xinyao Fan

Allan Macleod

Robert Gentleman

Ross Ihaka

latentUpdateBifactor function

<dl><dt>udata</dt>
<dd>nxd matrix with valies in (0,1)</dd><dt>cparvec</dt>
<dd>parameters for linking copulas; order is global_par1, global_par2, local_par1, local_par2</dd><dt>grsize</dt>
<dd>group size vector of length mgrp</dd><dt>family</dt>
<dd>codes for linking copula (VineCopula)</dd><dt>nq</dt>
<dd>number of Gaussian-Legendre points</dd></dl>

Arguments

Conditional expectation proxies for bi-factor copula models   with linking copulas in different copula families — latentUpdateBifactor

<dl>

<dt>udata</dt>
<dd>nxd matrix with valies in (0,1)</dd>

<dt>cparvec</dt>
<dd>parameters for linking copulas; order is global_par1, global_par2, local_par1, local_par2</dd>

<dt>grsize</dt>
<dd>group size vector of length mgrp</dd>

<dt>family</dt>
<dd>codes for linking copula (VineCopula)</dd>

<dt>nq</dt>
<dd>number of Gaussian-Legendre points</dd>

</dl>

latentUpdateBifactor: Conditional expectation proxies for bi-factor copula models with linking copulas in different copula families

Description

Usage

Value

Arguments

Examples