Showing 6 of total 6 results (show query)
astamm
nloptr:R Interface to NLopt
Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/> for more information on the available algorithms. Building from included sources requires 'CMake'. On Linux and 'macOS', if a suitable system build of NLopt (2.7.0 or later) is found, it is used; otherwise, it is built from included sources via 'CMake'. On Windows, NLopt is obtained through 'rwinlib' for 'R <= 4.1.x' or grabbed from the appropriate toolchain for 'R >= 4.2.0'.
Maintained by Aymeric Stamm. Last updated 13 days ago.
107 stars 17.17 score 1.1k scripts 1.8k dependents
cran
evd:Functions for Extreme Value Distributions
Extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.
Maintained by Alec Stephenson. Last updated 6 months ago.
2 stars 7.58 score 84 dependents
tysonstanley
MarginalMediation:Marginal Mediation
Provides the ability to perform "Marginal Mediation"--mediation wherein the indirect and direct effects are in terms of the average marginal effects (Bartus, 2005, <https://EconPapers.repec.org/RePEc:tsj:stataj:v:5:y:2005:i:3:p:309-329>). The style of the average marginal effects stems from Thomas Leeper's work on the "margins" package. This framework allows the use of categorical mediators and outcomes with little change in interpretation from the continuous mediators/outcomes. See <doi:10.13140/RG.2.2.18465.92001> for more details on the method.
Maintained by Tyson S Barrett. Last updated 3 years ago.
average-marginal-effectsmarginsmediationmediation-analysismediatorpartial-effectsrstudio
3 stars 4.29 score 13 scripts
qingzhaoyu
mma:Multiple Mediation Analysis
Used for general multiple mediation analysis. The analysis method is described in Yu and Li (2022) (ISBN: 9780367365479) "Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS", published by Chapman and Hall/CRC; and Yu et al.(2017) <DOI:10.1016/j.sste.2017.02.001> "Exploring racial disparity in obesity: a mediation analysis considering geo-coded environmental factors", published on Spatial and Spatio-temporal Epidemiology, 21, 13-23.
Maintained by Qingzhao Yu. Last updated 2 years ago.
1 stars 3.96 score 61 scripts 1 dependents
sens
qtlDesign:Design of QTL (Quantitative Trait Locus) Experiments
Design of QTL (quantitative trait locus) experiments involves choosing which strains to cross, the type of cross, genotyping strategies, phenotyping strategies, and the number of progeny to raise and phenotype. This package provides tools to help make such choices. Sen and others (2007) <doi:10.1007/s00335-006-0090-y>.
Maintained by Saunak Sen. Last updated 12 months ago.
1 stars 2.90 score 32 scripts
vishakhpk
TSeriesMMA:Multiscale Multifractal Analysis of Time Series Data
Multiscale multifractal analysis (MMA) (Gierałtowski et al., 2012)<DOI:10.1103/PhysRevE.85.021915> is a time series analysis method, designed to describe scaling properties of fluctuations within the signal analyzed. The main result of this procedure is the so called Hurst surface h(q,s) , which is a dependence of the local Hurst exponent h (fluctuation scaling exponent) on the multifractal parameter q and the scale of observation s (data window width).
Maintained by Vishakh Padmakumar. Last updated 8 years ago.
1.70 score 1 scripts