univariateML - Maximum Likelihood Estimation for Univariate Densities

User-friendly maximum likelihood estimation (Fisher (1921) <doi:10.1098/rsta.1922.0009>) of univariate densities.

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densityestimationmaximum-likelihood

7.42 score 9 stars 9 dependents 72 scripts 941 downloads

kdensity - Kernel Density Estimation with Parametric Starts and Asymmetric Kernels

Handles univariate non-parametric density estimation with parametric starts and asymmetric kernels in a simple and flexible way. Kernel density estimation with parametric starts involves fitting a parametric density to the data before making a correction with kernel density estimation, see Hjort & Glad (1995) <doi:10.1214/aos/1176324627>. Asymmetric kernels make kernel density estimation more efficient on bounded intervals such as (0, 1) and the positive half-line. Supported asymmetric kernels are the gamma kernel of Chen (2000) <doi:10.1023/A:1004165218295>, the beta kernel of Chen (1999) <doi:10.1016/S0167-9473(99)00010-9>, and the copula kernel of Jones & Henderson (2007) <doi:10.1093/biomet/asm068>. User-supplied kernels, parametric starts, and bandwidths are supported.

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asymmetric-kernelsdensity-estimationkernel-density-estimationnon-parametric

7.01 score 17 stars 2 dependents 199 scripts 574 downloads

nakagami - Functions for the Nakagami Distribution

Density, distribution function, quantile function and random generation for the Nakagami distribution of Nakagami (1960) <doi:10.1016/B978-0-08-009306-2.50005-4>.

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4.18 score 10 dependents 3 scripts 922 downloads

semTests - Goodness-of-Fit Testing for Structural Equation Models

Supports eigenvalue block-averaging p-values (Foldnes, Grønneberg, 2018) <doi:10.1080/10705511.2017.1373021>, penalized eigenvalue block-averaging p-values (Foldnes, Moss, Grønneberg, 2024) <doi:10.1080/10705511.2024.2372028>, penalized regression p-values (Foldnes, Moss, Grønneberg, 2024) <doi:10.1080/10705511.2024.2372028>, as well as traditional p-values such as Satorra-Bentler. All p-values can be calculated using unbiased or biased gamma estimates (Du, Bentler, 2022) <doi:10.1080/10705511.2022.2063870> and two choices of chi square statistics.

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3.19 score 31 scripts 168 downloads

publipha - Bayesian Meta-Analysis with Publications Bias and P-Hacking

Tools for Bayesian estimation of meta-analysis models that account for publications bias or p-hacking. For publication bias, this package implements a variant of the p-value based selection model of Hedges (1992) <doi:10.1214/ss/1177011364> with discrete selection probabilities. It also implements the mixture of truncated normals model for p-hacking described in Moss and De Bin (2019) <arXiv:1911.12445>.

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cpp

3.18 score 3 stars 3 scripts 235 downloads

attenuation - Correcting for Attenuation Due to Measurement Error

Confidence curves, confidence intervals and p-values for correlation coefficients corrected for attenuation due to measurement error. Implements the methods described in Moss (2019, <arxiv:1911.01576>).

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3.00 score 2 stars 1 scripts 227 downloads

subformula - Create Subformulas of a Formula

A formula 'sub' is a subformula of 'formula' if all the terms on the right hand side of 'sub' are terms of 'formula' and their left hand sides are identical. Creation of subformulas from a parent formula is useful in for instance model selection.

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2.70 score 1 stars 1 scripts 132 downloads

conogive - Congeneric Normal-Ogive Model

The congeneric normal-ogive model is a popular model for psychometric data (McDonald, R. P. (1997) <doi:10.1007/978-1-4757-2691-6_15>). This model estimates the model, calculates theoretical and concrete reliability coefficients, and predicts the latent variable of the model. This is the companion package to Moss (2020) <doi:10.31234/osf.io/nvg5d>.

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2.70 score 2 scripts 209 downloads