Simulation-Based Fitting of Parametric Models with Minimum Prior Information

Implements an algorithm for fitting a generative model with an intractable likelihood using only box constraints on the parameters. The implemented algorithm consists of two phases. The first phase (global search) aims to identify the region containing the best solution, while the second phase (local search) refines this solution using a trust-region version of the Fisher scoring method to solve a quasi-likelihood equation. See Guido Masarotto (2025) for the details of the algorithm and supporting results.


Reference manual

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install.packages("ifit")

1.0.0 by Guido Masarotto, a year ago


Browse source code at https://github.com/cran/ifit


Authors: Guido Masarotto [aut, cre] (ORCID:


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, lpSolve, parallel, splines, stats, graphics

Suggests lattice

Linking to Rcpp


See at CRAN