ifit-package

The main package function <code>ifit</code> can be used to fit complex
parametric models from which observations can be simulated. The
implemented algorithm integrates a global search phase and a local search phase.
It can hence be used when only scarce prior information is
available.

package

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) <doi:10.48550/arXiv.2511.08180> for the details of the algorithm and supporting results.

Guido Masarotto  and Cristiano
        Varin sammyuniveit

ifit

Simulation-Based Fitting of Parametric Models with Minimum Prior
Information

Guido Masarotto

ifit-package function

Maintainer: Guido Masarotto <a href="/link/guido.masarotto%40unipd.it?package=ifit&version=1.0.0" data-mini-rdoc="ifit::guido.masarotto@unipd.it">guido.masarotto@unipd.it</a> (<a href="https://orcid.org/0000-0003-4697-1606">ORCID</a>)

Author

ifit-package — ifit-package

Maintainer: Guido Masarotto <a href='mailto:guido.masarotto@unipd.it'>guido.masarotto@unipd.it</a> (<a href='https://orcid.org/0000-0003-4697-1606'>ORCID</a>)

ifit-package: ifit-package

Description

Arguments

Author

References