# lambda_QUT_covariates: Computes the threshold \$lambda_QUT\$ with parametric bootstrap... In genevievelrobin/lori: Low-rank Interaction Contingency Tables (Title Case)

## Description

Computes the threshold \$lambda_QUT\$ with parametric bootstrap when covariates are available. If you don't have any covariates, use the function `lambda_QUT` which will be significantly faster.

## Usage

 ```1 2``` ```lambda_QUT_covariates(Y, projection = default_projection, q = 0.95, n = 100) ```

## Arguments

 `Y` A matrix of counts (contingency table). `projection` A projection function on the space orthogonal to covariates. By default centers by rows and columns `q` A number between `0` and `1`. The quantile of the distribution of \$lambda_QUT\$ to take. `n` An integer. The number of parametric bootstrap samples to draw.

## Value

the value of \$lambda_QUT\$ to use in LoRI.

## Examples

 ```1 2 3 4 5``` ```X = matrix(rnorm(rep(0, 15)), 5) Y = matrix(rpois(length(c(X)), exp(c(X))), 5) lambda = lambda_QUT_covariates(Y, n=5) lambda = lambda_QUT_covariates(Y, n=100) ```

genevievelrobin/lori documentation built on April 2, 2018, 7:30 p.m.