simulate_p_mvn

Simulate p-values using multivariate normal distribution

internal

Provides a comprehensive framework for time series omics analysis,
integrating changepoint detection, smooth and shape-constrained trends,
and uncertainty quantification. It supports gene- and transcript-level inferences,
p-value aggregation for improved power, and both case-only and case-control designs.
It includes an interactive 'shiny' interface. The methods are described in Yates et al. (2024) <doi:10.1101/2024.12.22.630003>.

Luke Yates

cpam

Changepoint Additive Models for Time Series Omics Data

Michael Charleston

Jazmine Humphreys

Steven Smith

simulate_p_mvn function

<dl><dt>score_table</dt>
<dd>Table of model scores</dd>
<dt>nsim</dt>
<dd>Number of simulations (default: 1e4)</dd>
<dt>reg</dt>
<dd>Regularization parameter for covariance matrix (default: 1e-3)</dd></dl>

Arguments

Simulate p-values using multivariate normal distribution — simulate_p_mvn

<dl>

<dt>score_table</dt>
<dd>Table of model scores</dd>


<dt>nsim</dt>
<dd>Number of simulations (default: 1e4)</dd>


<dt>reg</dt>
<dd>Regularization parameter for covariance matrix (default: 1e-3)</dd>

</dl>

simulate_p_mvn: Simulate p-values using multivariate normal distribution

Description

Usage

Value

Arguments

Details