Iterative Proportional Fitting Algorithms for Nested Structures

Documentation for package ‘mlfit’ version 0.5.3

mlfit-package	mlfit: Iterative Proportional Fitting Algorithms for Nested Structures
as_flat_ml_fit_problem	Return a flattened representation of a multi-level fitting problem instance
compute_margins	Compute margins for a weighting of a multi-level fitting problem
dss	Calibrate sample weights
flatten_ml_fit_problem	Return a flattened representation of a multi-level fitting problem instance
format.ml_fit	Estimate weights for a fitting problem
format.ml_problem	Create an instance of a fitting problem
gginv	Generalized Inverse of a Matrix using a custom tolerance or SVD implementation
is_ml_fit	Estimate weights for a fitting problem
is_ml_problem	Create an instance of a fitting problem
margin_to_df	Compute margins for a weighting of a multi-level fitting problem
mlfit	mlfit: Iterative Proportional Fitting Algorithms for Nested Structures
ml_fit	Estimate weights for a fitting problem
ml_fit_dss	Estimate weights for a fitting problem
ml_fit_entropy_o	Estimate weights for a fitting problem
ml_fit_hipf	Estimate weights for a fitting problem
ml_fit_ipu	Estimate weights for a fitting problem
ml_problem	Create an instance of a fitting problem
ml_replicate	Replicate records in a reference sample based on its fitted weights
print.ml_fit	Estimate weights for a fitting problem
print.ml_problem	Create an instance of a fitting problem
special_field_names	Create an instance of a fitting problem
toy_example	Access to toy examples bundled in this package