Showing 27 of total 27 results (show query)
topepo
caret:Classification and Regression Training
Misc functions for training and plotting classification and regression models.
Maintained by Max Kuhn. Last updated 4 months ago.
1.6k stars 19.24 score 61k scripts 303 dependents
stan-dev
rstanarm:Bayesian Applied Regression Modeling via Stan
Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.
Maintained by Ben Goodrich. Last updated 11 days ago.
bayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-statisticsmultilevel-modelsrstanrstanarmstanstatistical-modelingcpp
393 stars 15.70 score 5.0k scripts 13 dependents
khliland
pls:Partial Least Squares and Principal Component Regression
Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS).
Maintained by Kristian Hovde Liland. Last updated 2 months ago.
37 stars 13.60 score 3.2k scripts 85 dependents
hzambran
hydroGOF:Goodness-of-Fit Functions for Comparison of Simulated and Observed Hydrological Time Series
S3 functions implementing both statistical and graphical goodness-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models. Missing values in observed and/or simulated values can be removed before computations. Comments / questions / collaboration of any kind are very welcomed.
Maintained by Mauricio Zambrano-Bigiarini. Last updated 11 months ago.
40 stars 10.29 score 796 scripts 8 dependents
jwiley
JWileymisc:Miscellaneous Utilities and Functions
Miscellaneous tools and functions, including: generate descriptive statistics tables, format output, visualize relations among variables or check distributions, and generic functions for residual and model diagnostics.
Maintained by Joshua F. Wiley. Last updated 4 days ago.
6 stars 7.78 score 241 scripts 4 dependents
tagteam
pec:Prediction Error Curves for Risk Prediction Models in Survival Analysis
Validation of risk predictions obtained from survival models and competing risk models based on censored data using inverse weighting and cross-validation. Most of the 'pec' functionality has been moved to 'riskRegression'.
Maintained by Thomas A. Gerds. Last updated 2 years ago.
7.42 score 512 scripts 26 dependentskhliland
multiblock:Multiblock Data Fusion in Statistics and Machine Learning
Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1) "Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences". This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting functions, several real data sets and six vignettes covering a range different applications.
Maintained by Kristian Hovde Liland. Last updated 2 months ago.
14 stars 6.68 score 19 scripts
arives
rr2:R2s for Regression Models
Three methods to calculate R2 for models with correlated errors, including Phylogenetic GLS, Phylogenetic Logistic Regression, Linear Mixed Models (LMMs), and Generalized Linear Mixed Models (GLMMs). See details in Ives 2018 <doi:10.1093/sysbio/syy060>.
Maintained by Anthony Ives. Last updated 2 years ago.
18 stars 6.67 score 104 scripts 1 dependents
cran
compositions:Compositional Data Analysis
Provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations) in the way proposed by J. Aitchison and V. Pawlowsky-Glahn.
Maintained by K. Gerald van den Boogaart. Last updated 1 years ago.
1 stars 6.35 score 36 dependents
dtkaplan
LSTbook:Data and Software for "Lessons in Statistical Thinking"
"Lessons in Statistical Thinking" D.T. Kaplan (2014) <https://dtkaplan.github.io/Lessons-in-statistical-thinking/> is a textbook for a first or second course in statistics that embraces data wrangling, causal reasoning, modeling, statistical adjustment, and simulation. 'LSTbook' supports the student-centered, tidy, pipeline-oriented computing style featured in the book.
Maintained by Daniel Kaplan. Last updated 3 days ago.
4 stars 6.32 score 27 scripts
murphymv
semEff:Automatic Calculation of Effects for Piecewise Structural Equation Models
Automatically calculate direct, indirect, and total effects for piecewise structural equation models, comprising lists of fitted models representing structured equations (Lefcheck, 2016 <doi:10/f8s8rb>). Confidence intervals are provided via bootstrapping.
Maintained by Mark V. Murphy. Last updated 7 months ago.
12 stars 6.20 score 29 scripts
fmmgroupva
FMM:Rhythmic Patterns Modeling by FMM Models
Provides a collection of functions to fit and explore single, multi-component and restricted Frequency Modulated Moebius (FMM) models. 'FMM' is a nonlinear parametric regression model capable of fitting non-sinusoidal shapes in rhythmic patterns. Details about the mathematical formulation of 'FMM' models can be found in Rueda et al. (2019) <doi:10.1038/s41598-019-54569-1>.
Maintained by Itziar Fernandez. Last updated 5 days ago.
2 stars 5.48 score
bfifield
hettx:Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation
Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <arXiv:1412.5000>, and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <arXiv:1605.06566> for testing whether there is unexplained variation in treatment effects across observations, and for characterizing the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.
Maintained by Ben Fifield. Last updated 2 years ago.
10 stars 5.32 score 21 scripts
nelson-n
lmForc:Linear Model Forecasting
Introduces in-sample, out-of-sample, pseudo out-of-sample, and benchmark model forecast tests and a new class for working with forecast data, Forecast.
Maintained by Nelson Rayl. Last updated 7 months ago.
6 stars 5.08 score 20 scripts
poissonconsulting
embr:Model Builder Utility Functions and Virtual Classes
Utility functions and virtual classes shared by model builder packages such as tmbr, jmbr and smbr.
Maintained by Joe Thorley. Last updated 2 months ago.
3 stars 4.61 score 4 scripts 3 dependentskhliland
HDANOVA:High-Dimensional Analysis of Variance
Functions and datasets to support Smilde, Marini, Westerhuis and Liland (2025, ISBN: 978-1-394-21121-0) "Analysis of Variance for High-Dimensional Data - Applications in Life, Food and Chemical Sciences". This implements and imports a collection of methods for HD-ANOVA data analysis with common interfaces, result- and plotting functions, multiple real data sets and four vignettes covering a range different applications.
Maintained by Kristian Hovde Liland. Last updated 17 days ago.
4.35 score 8 scripts 1 dependents
alexander-pastukhov
TriDimRegression:Bayesian Statistics for 2D/3D Transformations
Fits 2D and 3D geometric transformations via 'Stan' probabilistic programming engine ( Stan Development Team (2021) <https://mc-stan.org>). Returns posterior distribution for individual parameters of the fitted distribution. Allows for computation of LOO and WAIC information criteria (Vehtari A, Gelman A, Gabry J (2017) <doi:10.1007/s11222-016-9696-4>) as well as Bayesian R-squared (Gelman A, Goodrich B, Gabry J, and Vehtari A (2018) <doi:10.1080/00031305.2018.1549100>).
Maintained by Alexander Pastukhov. Last updated 2 years ago.
bidimensional-regressiontridimenisional-regressioncpp
4.18 score 7 scriptscran
nsRFA:Non-Supervised Regional Frequency Analysis
A collection of statistical tools for objective (non-supervised) applications of the Regional Frequency Analysis methods in hydrology. The package refers to the index-value method and, more precisely, helps the hydrologist to: (1) regionalize the index-value; (2) form homogeneous regions with similar growth curves; (3) fit distribution functions to the empirical regional growth curves. Most of the methods are those described in the Flood Estimation Handbook (Centre for Ecology & Hydrology, 1999, ISBN:9781906698003). Homogeneity tests from Hosking and Wallis (1993) <doi:10.1029/92WR01980> and Viglione et al. (2007) <doi:10.1029/2006WR005095> are available.
Maintained by Alberto Viglione. Last updated 11 months ago.
2 stars 3.48 scorekhliland
ER:Effect + Residual Modelling
Multivariate modeling of data after deflation of interfering effects. EF Mosleth et al. (2021) <doi:10.1038/s41598-021-82388-w> and EF Mosleth et al. (2020) <doi:10.1016/B978-0-12-409547-2.14882-6>.
Maintained by Kristian Hovde Liland. Last updated 2 years ago.
3.00 score 1 scripts
hjboonstra
hbsae:Hierarchical Bayesian Small Area Estimation
Functions to compute small area estimates based on a basic area or unit-level model. The model is fit using restricted maximum likelihood, or in a hierarchical Bayesian way. In the latter case numerical integration is used to average over the posterior density for the between-area variance. The output includes the model fit, small area estimates and corresponding mean squared errors, as well as some model selection measures. Additional functions provide means to compute aggregate estimates and mean squared errors, to minimally adjust the small area estimates to benchmarks at a higher aggregation level, and to graphically compare different sets of small area estimates.
Maintained by Harm Jan Boonstra. Last updated 3 years ago.
2 stars 2.53 score 28 scripts 2 dependentscran
PerMat:Performance Metrics in Predictive Modeling
Performance metric provides different performance measures like mean squared error, root mean square error, mean absolute deviation, mean absolute percentage error etc. of a fitted model. These can provide a way for forecasters to quantitatively compare the performance of competing models. For method details see (i) Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.
Maintained by Pankaj Das. Last updated 10 months ago.
2.00 score
chelbert
DiceEval:Construction and Evaluation of Metamodels
Estimation, validation and prediction of models of different types : linear models, additive models, MARS,PolyMARS and Kriging.
Maintained by C. Helbert. Last updated 1 years ago.
1.81 score 64 scripts
mattansb
MSBMisc:Some functions I wrote that I find useful
misc. functions.
Maintained by Mattan S. Ben-Shachar. Last updated 2 years ago.
1 stars 1.70 score 2 scripts
cecile-ch
PHeval:Evaluation of the Proportional Hazards Assumption and Test for Comparing Survival Curves with a Standardized Score Process
Provides tools for the test for the comparison of survival curves, the evaluation of the goodness-of-fit and the predictive capacity of the proportional hazards model.
Maintained by Cecile Chauvel. Last updated 7 months ago.
1.30 score 4 scriptscran
TExPosition:Two-Table ExPosition
An extension of ExPosition for two table analyses, specifically, discriminant analyses.
Maintained by Derek Beaton. Last updated 6 years ago.
1.30 scorecran
pAnalysis:Benchmarking and Rescaling R2 using Noise Percentile Analysis
Provides the tools needed to benchmark the R2 value corresponding to a certain acceptable noise level while also providing a rescaling function based on that noise level yielding a new value of R2 we refer to as R2k which is independent of both the number of degrees of freedom and the noise distribution function.
Maintained by Joseph G Kreke. Last updated 9 years ago.
1.00 score