qcondbvtcop

bivariate Student t copula conditional quantile

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

qcondbvtcop function

<dl><dt>p</dt>
<dd>0&lt;p&lt;1, could be a vector</dd><dt>u</dt>
<dd>0&lt;u&lt;1, could be a vector</dd><dt>cpar</dt>
<dd>copula parameter: 2-vector with -1&lt;rho&lt;1, df&gt;0</dd></dl>

Arguments

C_[2|1]^[-1](p|u) for bivariate Student t copula — qcondbvtcop

<dl>

<dt>p</dt>
<dd>0&lt;p&lt;1, could be a vector</dd>

<dt>u</dt>
<dd>0&lt;u&lt;1, could be a vector</dd>

<dt>cpar</dt>
<dd>copula parameter: 2-vector with -1&lt;rho&lt;1, df&gt;0</dd>

</dl>

qcondbvtcop: C_[2|1]^[-1](p|u) for bivariate Student t copula

Description

Usage

Value

Arguments