bCond.pobs

Let $A_1, ..., A_p$ be $p$ events forming a partition of
a probability space and $X_1, ..., X_d$ be $d$ random variables.
Assume that we observe $n$ i.i.d. replications of $(X_1, ..., X_d)$,
and that for each $i=1, ..., d$,
$$V_{i,j|A} = F_{X_j | A_k}(X_{i,j} | A_k),$$
we also know which of the $A_k$ was realized.
This function computes the pseudo-observations
where $k$ is such that the event $A_k$
is realized for the $i$-th observation.

Provides functions for the estimation of conditional copulas models,
various estimators of conditional Kendall's tau
(proposed in Derumigny and Fermanian (2019a, 2019b, 2020)
<doi:10.1515/demo-2019-0016>,
<doi:10.1016/j.csda.2019.01.013>,
<doi:10.1016/j.jmva.2020.104610>),
test procedures for the simplifying assumption
(proposed in Derumigny and Fermanian (2017) <doi:10.1515/demo-2017-0011>
and Derumigny, Fermanian and Min (2022) <doi:10.1002/cjs.11742>),
and measures of non-simplifyingness
(proposed in Derumigny (2025) <doi:10.48550/arXiv.2504.07704>).

Alexis Derumigny

CondCopulas

Estimation and Inference for Conditional Copula Models

Jean-David Fermanian

Aleksey Min

Rutger van der Spek

bCond.pobs function

<dl><dt>X</dt>
<dd>matrix of size <code>n * d</code> observations of conditioned variables.</dd>
<dt>partition</dt>
<dd>matrix of size <code>n * p</code>,
where <code>p</code> is the number of conditioning events that are considered.
partition[i,k] should be the indicator of whether the <code>i</code>-th observation
belongs or not to the <code>k</code>-th conditioning event.</dd></dl>

Arguments

Computing the pseudo-observations in case of discrete
conditioning events — bCond.pobs

<dl>

<dt>X</dt>
<dd>matrix of size <code>n * d</code> observations of conditioned variables.</dd>


<dt>partition</dt>
<dd>matrix of size <code>n * p</code>,
where <code>p</code> is the number of conditioning events that are considered.
partition[i,k] should be the indicator of whether the <code>i</code>-th observation
belongs or not to the <code>k</code>-th conditioning event.</dd>

</dl>

bCond.pobs: Computing the pseudo-observations in case of discrete conditioning events

Description

Usage

Value

Arguments

References

See Also

Examples