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ssmodels - Sample Selection Models

In order to facilitate the adjustment of the sample selection models existing in the literature, we created the 'ssmodels' package. Our package allows the adjustment of the classic Heckman model (Heckman (1976), Heckman (1979) <doi:10.2307/1912352>), and the estimation of the parameters of this model via the maximum likelihood method and two-step method, in addition to the adjustment of the Heckman-t models introduced in the literature by Marchenko and Genton (2012) <doi:10.1080/01621459.2012.656011> and the Heckman-Skew model introduced in the literature by Ogundimu and Hutton (2016) <doi:10.1111/sjos.12171>. We also implemented functions to adjust the generalized version of the Heckman model, introduced by Bastos, Barreto-Souza, and Genton (2021) <doi:10.5705/ss.202021.0068>, that allows the inclusion of covariables to the dispersion and correlation parameters, and a function to adjust the Heckman-BS model introduced by Bastos and Barreto-Souza (2020) <doi:10.1080/02664763.2020.1780570> that uses the Birnbaum-Saunders distribution as a joint distribution of the selection and primary regression variables. This package extends and complements existing R packages such as 'sampleSelection' (Toomet and Henningsen, 2008) and 'ssmrob' (Zhelonkin et al., 2016), providing additional robust and flexible sample selection models.

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4.18 score 1 stars 15 scripts 398 downloads

stringArt - Tools for Generating String Art Figures

Provides tools to generate, visualize, and audit geometric string art figures for mathematics teaching. The package includes functions for circular, cardioid-like, elliptical, triangular, polygonal, star, parabolic, net-based, radial, hexagonal, lotus-like, rose-like, spiral, Lissajous, grid-based, decimal, and contour-based string art patterns. Each function returns peg coordinates, connection tables, total string length, audit information, and metadata, supporting educational applications in geometry, analytic geometry, modular arithmetic, trigonometry, rational numbers, and visual mathematics.

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4.18 score 257 downloads

heckmanGE - Estimation and Inference for Heckman Selection Models with Cluster-Robust Variance

Tools for the estimation of Heckman selection models with robust variance-covariance matrices. It includes functions for computing the bread and meat matrices, as well as clustered standard errors for generalized Heckman models, see Fernando de Souza Bastos and Wagner Barreto-Souza and Marc G. Genton (2022, ISSN: <https://www.jstor.org/stable/27164235>). The package also offers cluster-robust inference with sandwich estimators, and tools for handling issues related to eigenvalues in covariance matrices.

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2.70 score 282 downloads