semiCor

semi-correlations (lower and upper) applied to data after normal scores transform

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

semiCor function

<dl><dt>bivdat</dt>
<dd>nx2 data set</dd><dt>inscore</dt>
<dd>TRUE if bivdat has already been converted to normal scores, default FALSE</dd></dl>

Arguments

Semi-correlations for two variables — semiCor

<dl>

<dt>bivdat</dt>
<dd>nx2 data set</dd>

<dt>inscore</dt>
<dd>TRUE if bivdat has already been converted to normal scores, default FALSE</dd>

</dl>

semiCor: Semi-correlations for two variables

Description

Usage

Value

Arguments

Examples