![](https://github.com/jonasmoss/univariateml/raw/HEAD/man/figures/logo.png)
univariateML - Maximum Likelihood Estimation for Univariate Densities
User-friendly maximum likelihood estimation (Fisher (1921) <doi:10.1098/rsta.1922.0009>) of univariate densities.
Last updated 4 months ago
densityestimationmaximum-likelihood
7.73 score 8 stars 7 dependents 53 scripts 812 downloads![](https://github.com/jonasmoss/nakagami/raw/HEAD/man/figures/logo.png)
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>.
Last updated 3 years ago
4.08 score 8 dependents 2 scripts 794 downloads![](https://github.com/jonasmoss/publipha/raw/HEAD/man/figures/logo.png)
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>.
Last updated 2 years ago
cpp
3.18 score 3 stars 3 scripts 189 downloads![](https://github.com/jonasmoss/subformula/raw/HEAD/man/figures/logo.png)
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.
Last updated 3 years ago
2.70 score 1 stars 1 scripts 135 downloads![](https://github.com/jonasmoss/attenuation/raw/HEAD/man/figures/logo.png)
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>).
Last updated 5 years ago
3.00 score 2 stars 1 scripts 256 downloads![](https://github.com/jonasmoss/conogive/raw/HEAD/man/figures/logo.png)
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>.
Last updated 5 years ago
2.70 score 2 scripts 139 downloads