mipfp

Transforming an array to a vector

Comparing deviations of mipfp objects

Computes the marginal matrix A and margins vector m of an estimation problem

Converting correlation to odds ratio

Converting correlation to pairwise probability

Update an N-way table given target margins

Computing confidence intervals for the estimated counts and probabilities (deprecated)

Extracting the linearly independant columns from a matrix

Multidimensional Iterative Proportional Fitting

Covariance matrix of the estimators produced by Ipfp (deprecated)

Estimating a contingency table using model-based approaches

Generating a multivariate Bernoulli joint-distribution

Converting odds ratio to correlation

Converting odds ratio to pairwise probability

Qaqish

Simulating a multivariate Bernoulli distribution

Transforming a vector to an array

Extract the coefficients of the estimates from an object of class mipfp

Computing confidence intervals for the mipfp estimates

Extracts the deviation between every target and generated margin

Expand a Table in a Data Frame

Flatten a table, array or matrix

Wald, Log-likelihood ratio and Person Chi-square statistics for mipfp object

Multidimensional Iterative Proportional Fitting and Alternative Models

Synthetic population of Namur (Belgium)

Summarizing objects of class mipfp

Calculate variance-covariance matrix for mipfp objects