combinate

Given X and Y, both matrices where the rows are counts of multinomial trials,
produce all combinations rowwise, concatenate the rows into a new matrix, and
calculate the log multinomial coefficients for the combination.

We consider the problem where we observe k vectors (possibly of different lengths), each representing an independent multinomial random vector. For a given function that takes in the concatenated vector of multinomial probabilities and outputs a real number, this is a Monte Carlo estimation procedure of an exact p-value and confidence interval. The resulting inference is valid even in small samples, when the parameter is on the boundary, and when the function is not differentiable at the parameter value, all situations where asymptotic methods and the bootstrap would fail. For more details see Sachs, Fay, and Gabriel (2025) <doi:10.48550/arXiv.2406.19141>.

Michael Sachs

xactonomial

Inference for Functions of Multinomial Parameters

Michael C Sachs

Michael P Fay

Erin E Gabriel

David B Dahl

combinate function

<dl><dt>X</dt>
<dd>Matrix 1</dd>
<dt>Y</dt>
<dd>Matrix 2</dd></dl>

Arguments

Arrange all combinations of rows of two matrices — combinate

<dl>

<dt>X</dt>
<dd>Matrix 1</dd>


<dt>Y</dt>
<dd>Matrix 2</dd>

</dl>

combinate: Arrange all combinations of rows of two matrices

Description

Usage

Value

Arguments

Examples