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 10 days ago

densityestimationmaximum-likelihood

8.10 score 8 stars 7 dependents 62 scripts 949 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.

Last updated 9 days ago

asymmetric-kernelsdensity-estimationkernel-density-estimationnon-parametric

6.87 score 16 stars 1 dependents 153 scripts 537 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>.

Last updated 3 years ago

4.08 score 8 dependents 2 scripts 933 downloads

alphaci - Confidence Intervals for Coefficient Alpha and Standardized Alpha

Calculate confidence intervals for alpha and standardized alpha using asymptotic theory or the studentized bootstrap, with or without transformations. Supports the asymptotic distribution-free method of Maydeu-Olivares, et al. (2007) <doi:10.1037/1082-989X.12.2.157>, the pseudo-elliptical method of Yuan & Bentler (2002) <doi:10.1007/BF02294845>, and the normal method of van Zyl et al. (1999) <doi:10.1007/BF02296146>, for both coefficient alpha and standardized alpha.

Last updated 1 years ago

4.00 score 1 scripts 297 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>.

Last updated 2 years ago

cpp

3.18 score 3 stars 3 scripts 204 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>).

Last updated 5 years ago

3.00 score 2 stars 1 scripts 217 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.

Last updated 3 years ago

2.70 score 1 stars 1 scripts 136 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>.

Last updated 5 years ago

2.70 score 2 scripts 163 downloads