Provides statistical methods to check if a parametric family of conditional density functions fits to some given dataset of covariates and response variables. Different test statistics can be used to determine the goodness-of-fit of the assumed model, see Andrews (1997) <doi:10.2307/2171880>, Bierens & Wang (2012) <doi:10.1017/S0266466611000168>, Dikta & Scheer (2021) <doi:10.1007/978-3-030-73480-0> and Kremling & Dikta (2024) <doi:10.48550/arXiv.2409.20262>. As proposed in these papers, the corresponding p-values are approximated using a parametric bootstrap method.
Package details |
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Author | Gitte Kremling [aut, cre, cph] (<https://orcid.org/0000-0002-0753-1520>) |
Maintainer | Gitte Kremling <gitte.kremling@web.de> |
License | MIT + file LICENSE |
Version | 1.0.0 |
URL | https://github.com/gkremling/gofreg https://gkremling.github.io/gofreg/ |
Package repository | View on CRAN |
Installation |
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