Showing 25 of total 25 results (show query)
richarddmorey
BayesFactor:Computation of Bayes Factors for Common Designs
A suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one-way designs, general ANOVA designs, and linear regression.
Maintained by Richard D. Morey. Last updated 1 years ago.
132 stars 13.71 score 1.7k scripts 21 dependents
tommyjones
textmineR:Functions for Text Mining and Topic Modeling
An aid for text mining in R, with a syntax that should be familiar to experienced R users. Provides a wrapper for several topic models that take similarly-formatted input and give similarly-formatted output. Has additional functionality for analyzing and diagnostics for topic models.
Maintained by Tommy Jones. Last updated 2 years ago.
106 stars 10.83 score 310 scripts 7 dependents
zeileis
betareg:Beta Regression
Beta regression for modeling beta-distributed dependent variables on the open unit interval (0, 1), e.g., rates and proportions, see Cribari-Neto and Zeileis (2010) <doi:10.18637/jss.v034.i02>. Moreover, extended-support beta regression models can accommodate dependent variables with boundary observations at 0 and/or 1. For the classical beta regression model, alternative specifications are provided: Bias-corrected and bias-reduced estimation, finite mixture models, and recursive partitioning for beta regression, see Grün, Kosmidis, and Zeileis (2012) <doi:10.18637/jss.v048.i11>.
Maintained by Achim Zeileis. Last updated 12 days ago.
10.63 score 904 scripts 22 dependents
cran
flexmix:Flexible Mixture Modeling
A general framework for finite mixtures of regression models using the EM algorithm is implemented. The E-step and all data handling are provided, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.
Maintained by Bettina Gruen. Last updated 30 days ago.
5 stars 8.19 score 113 dependentstommyjones
tidylda:Latent Dirichlet Allocation Using 'tidyverse' Conventions
Implements an algorithm for Latent Dirichlet Allocation (LDA), Blei et at. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>, using style conventions from the 'tidyverse', Wickham et al. (2019)<doi:10.21105/joss.01686>, and 'tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>. Fitting is done via collapsed Gibbs sampling. Also implements several novel features for LDA such as guided models and transfer learning.
Maintained by Tommy Jones. Last updated 2 months ago.
41 stars 7.36 score 53 scripts
bioc
flowClust:Clustering for Flow Cytometry
Robust model-based clustering using a t-mixture model with Box-Cox transformation. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'.
Maintained by Greg Finak. Last updated 5 months ago.
immunooncologyclusteringvisualizationflowcytometry
7.31 score 83 scripts 6 dependents
optad
adoptr:Adaptive Optimal Two-Stage Designs
Optimize one or two-arm, two-stage designs for clinical trials with respect to several implemented objective criteria or custom objectives. Optimization under uncertainty and conditional (given stage-one outcome) constraints are supported. See Pilz et al. (2019) <doi:10.1002/sim.8291> and Kunzmann et al. (2021) <doi:10.18637/jss.v098.i09> for details.
Maintained by Maximilian Pilz. Last updated 6 months ago.
1 stars 7.09 score 39 scripts 1 dependents
ingmarvisser
depmixS4:Dependent Mixture Models - Hidden Markov Models of GLMs and Other Distributions in S4
Fits latent (hidden) Markov models on mixed categorical and continuous (time series) data, otherwise known as dependent mixture models, see Visser & Speekenbrink (2010, <DOI:10.18637/jss.v036.i07>).
Maintained by Ingmar Visser. Last updated 4 years ago.
12 stars 6.85 score 308 scripts 4 dependents
shaunpwilkinson
aphid:Analysis with Profile Hidden Markov Models
Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).
Maintained by Shaun Wilkinson. Last updated 9 months ago.
22 stars 6.58 score 38 scripts 3 dependents
thothorn
modeltools:Tools and Classes for Statistical Models
A collection of tools to deal with statistical models. The functionality is experimental and the user interface is likely to change in the future. The documentation is rather terse, but packages `coin' and `party' have some working examples. However, if you find the implemented ideas interesting we would be very interested in a discussion of this proposal. Contributions are more than welcome!
Maintained by Torsten Hothorn. Last updated 5 years ago.
6.56 score 84 scripts 254 dependents
blue-matter
SAMtool:Stock Assessment Methods Toolkit
Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.
Maintained by Quang Huynh. Last updated 1 months ago.
3 stars 6.39 score 36 scripts 1 dependentscran
topicmodels:Topic Models
Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.
Maintained by Bettina Grün. Last updated 8 months ago.
8 stars 6.37 score 16 dependents
andreanini
idiolect:Forensic Authorship Analysis
Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta <doi:10.1080/09296174.2011.533591> or Koppel and Winter's (2014) Impostors Method <doi:10.1002/asi.22954>, as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.
Maintained by Andrea Nini. Last updated 23 days ago.
14 stars 6.12 score 3 scripts
jkrijthe
RSSL:Implementations of Semi-Supervised Learning Approaches for Classification
A collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.
Maintained by Jesse Krijthe. Last updated 1 years ago.
58 stars 6.05 score 128 scripts 1 dependents
rich-payne
dreamer:Dose Response Models for Bayesian Model Averaging
Fits dose-response models utilizing a Bayesian model averaging approach as outlined in Gould (2019) <doi:10.1002/bimj.201700211> for both continuous and binary responses. Longitudinal dose-response modeling is also supported in a Bayesian model averaging framework as outlined in Payne, Ray, and Thomann (2024) <doi:10.1080/10543406.2023.2292214>. Functions for plotting and calculating various posterior quantities (e.g. posterior mean, quantiles, probability of minimum efficacious dose, etc.) are also implemented. Copyright Eli Lilly and Company (2019).
Maintained by Richard Daniel Payne. Last updated 3 months ago.
bayesiandose-response-modelingjagscpp
9 stars 5.26 score 5 scriptsrich-payne
beaver:Bayesian Model Averaging of Covariate Adjusted Negative-Binomial Dose-Response
Dose-response modeling for negative-binomial distributed data with a variety of dose-response models. Covariate adjustment and Bayesian model averaging is supported. Functions are provided to easily obtain inference on the dose-response relationship and plot the dose-response curve.
Maintained by Hollins Showalter. Last updated 10 months ago.
1 stars 3.89 score 78 scriptsbioc
MADSEQ:Mosaic Aneuploidy Detection and Quantification using Massive Parallel Sequencing Data
The MADSEQ package provides a group of hierarchical Bayeisan models for the detection of mosaic aneuploidy, the inference of the type of aneuploidy and also for the quantification of the fraction of aneuploid cells in the sample.
Maintained by Yu Kong. Last updated 5 months ago.
genomicvariationsomaticmutationvariantdetectionbayesiancopynumbervariationsequencingcoveragejagscpp
4 stars 3.60 score 1 scriptscran
HMM:Hidden Markov Models
Easy to use library to setup, apply and make inference with discrete time and discrete space Hidden Markov Models.
Maintained by Lin Himmelmann. Last updated 3 years ago.
3 stars 3.56 score 4 dependents
hadley
classifly:Explore Classification Models in High Dimensions
Given $p$-dimensional training data containing $d$ groups (the design space), a classification algorithm (classifier) predicts which group new data belongs to. Generally the input to these algorithms is high dimensional, and the boundaries between groups will be high dimensional and perhaps curvilinear or multi-faceted. This package implements methods for understanding the division of space between the groups.
Maintained by Hadley Wickham. Last updated 3 years ago.
10 stars 3.54 score 35 scripts
stan-dev
posteriordb:R functionality for posteriordb
R functionality of easy handling of the posteriordb posteriors.
Maintained by Mans Magnusson. Last updated 2 years ago.
8 stars 3.37 score 59 scriptsrich-payne
yodel:A General Bayesian Model Averaging Helper
Provides helper functions to perform Bayesian model averaging using Markov chain Monte Carlo samples from separate models. Calculates weights and obtains draws from the model-averaged posterior for quantities of interest specified by the user. Weight calculations can be done using marginal likelihoods or log-predictive likelihoods as in Ando, T., & Tsay, R. (2010) <doi:10.1016/j.ijforecast.2009.08.001>.
Maintained by Richard Payne. Last updated 12 months ago.
3.18 score 1 dependents
alessandromagrini
gbmt:Group-Based Multivariate Trajectory Modeling
Estimation and analysis of group-based multivariate trajectory models (Nagin, 2018 <doi:10.1177/0962280216673085>; Magrini, 2022 <doi:10.1007/s10182-022-00437-9>). The package implements an Expectation-Maximization (EM) algorithm allowing unbalanced panel and missing values, and provides several functionalities for prediction and graphical representation.
Maintained by Alessandro Magrini. Last updated 4 months ago.
3 stars 1.52 score 11 scriptscran
evdbayes:Bayesian Analysis in Extreme Value Theory
Provides functions for the Bayesian analysis of extreme value models, using Markov chain Monte Carlo methods. Allows the construction of both uninformative and informed prior distributions for common statistical models applied to extreme event data, including the generalized extreme value distribution.
Maintained by Alec Stephenson. Last updated 2 years ago.
1.00 scorecran
bqtl:Bayesian QTL Mapping Toolkit
QTL mapping toolkit for inbred crosses and recombinant inbred lines. Includes maximum likelihood and Bayesian tools.
Maintained by Charles C. Berry. Last updated 6 months ago.
1.00 score