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MCARtest (version 1.3)

Optimal Nonparametric Testing of Missing Completely at Random

Description

Provides functions for carrying out nonparametric hypothesis tests of the MCAR hypothesis based on the theory of Frechet classes and compatibility. Also gives functions for computing halfspace representations of the marginal polytope and related geometric objects.

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Install

install.packages('MCARtest')

Monthly Downloads

571

Version

1.3

License

MIT + file LICENSE

Maintainer

Thomas Berrett

Last Published

June 26th, 2025

Functions in MCARtest (1.3)

Calculates the total cardinality of the sample spaces.

Computes the collection of patterns, means, variances, covariance and correlation matrices for a given dataset with missing values.

A function computing the regularised incompatibility index for collections of correlation matrices.

Carry out a test of MCAR checking compatibility of correlation matrices.

Internal function multiplying a mass function by the sparse matrix A.

Carry out a test of MCAR checking consistency of mean vectors.

Carry out Little's test of MCAR.

Calculates the individual cardinalities of the sample spaces.

A function indexing the columns of A

A function indexing the rows of A

A function computing the incompatibility index for sequences of correlation matrices.

Carry out a test of MCAR checking consistency of variance vectors.

Compute the log likelihood of a probability mass function, under MCAR, given complete and incomplete data

Compute the log likelihood of a probability mass function, without assuming MCAR, given complete and incomplete data

Generates the column indices used internally to generate the sparse matrix A.

Generate the matrix A, whose columns are the vertices of the marginal polytope.

Generate the matrix A, whose columns are the vertices of the marginal polytope, as a sparse matrix.

InconsMinkSumHrep

Calculate the H-representation of the general (possibly inconsistent) Minkowski sum

EquivalenceClass

Simplifies H-representation by exploiting symmetry

Calculate the critical value for our improved test

Perform one step of the EM algorithm for finding the MLE under MCAR in a contingency table.

Calculate the critical value for our simple test

Carry out Fuchs's test of MCAR in a contingency table, given complete and incomplete observations.

ConsMinkSumHrep

Calculate the H-representation of the consistent Minkowski sum

Round errors in halfspace representations

aMatrixSparseRevLex

Generates the row indices used internally to generate the sparse matrix A.

Carry out a test of MCAR in a contingency table, given incomplete observations.

Computes an inconsistency index for sequences of variances.

Calculate the H-representation of the marginal polytope

Compute the MLE under MCAR in a contingency table using the EM algorithm, given complete and incomplete observations.

A function computing the incompatibility index and associated closest joint mass function using the dual formulation

A function computing the incompatibility index

Computes an inconsistency index for a collection of means.

Compute the columnwise average of a collection of vectors.