bifactorScore

Proxies (in (0,1)) for bi-factor copula model based on Gaussian bi-factor score

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

bifactorScore function

<dl><dt>udata</dt>
<dd>nxd matrix in (0,1); n is sample size, d is dimension</dd><dt>start</dt>
<dd>starting values for fitting the bi-factor Gaussian model</dd><dt>grsize</dt>
<dd>G-vector with group sizes with G groups</dd><dt>prlev</dt>
<dd>printlevel in call to nlm</dd></dl>

Arguments

Proxies for bi-factor copula model based on Gaussian bi-factor score — bifactorScore

<dl>

<dt>udata</dt>
<dd>nxd matrix in (0,1); n is sample size, d is dimension</dd>

<dt>start</dt>
<dd>starting values for fitting the bi-factor Gaussian model</dd>

<dt>grsize</dt>
<dd>G-vector with group sizes with G groups</dd>

<dt>prlev</dt>
<dd>printlevel in call to nlm</dd>

</dl>

bifactorScore: Proxies for bi-factor copula model based on Gaussian bi-factor score

Description

Usage

Value

Arguments

Examples