Showing 38 of total 38 results (show query)
yrosseel
lavaan:Latent Variable Analysis
Fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.
Maintained by Yves Rosseel. Last updated 4 days ago.
factor-analysisgrowth-curve-modelslatent-variablesmissing-datamultilevel-modelsmultivariate-analysispath-analysispsychometricsstatistical-modelingstructural-equation-modeling
454 stars 16.82 score 8.4k scripts 218 dependents
philchalmers
mirt:Multidimensional Item Response Theory
Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.
Maintained by Phil Chalmers. Last updated 3 days ago.
212 stars 14.93 score 2.5k scripts 40 dependents
bbolker
bbmle:Tools for General Maximum Likelihood Estimation
Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.
Maintained by Ben Bolker. Last updated 2 months ago.
25 stars 13.36 score 1.4k scripts 117 dependents
biodiverse
unmarked:Models for Data from Unmarked Animals
Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
Maintained by Ken Kellner. Last updated 11 days ago.
4 stars 13.02 score 652 scripts 12 dependents
alexiosg
rugarch:Univariate GARCH Models
ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting.
Maintained by Alexios Galanos. Last updated 3 months ago.
26 stars 12.25 score 1.3k scripts 16 dependents
bioc
variancePartition:Quantify and interpret drivers of variation in multilevel gene expression experiments
Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.
Maintained by Gabriel E. Hoffman. Last updated 3 months ago.
rnaseqgeneexpressiongenesetenrichmentdifferentialexpressionbatcheffectqualitycontrolregressionepigeneticsfunctionalgenomicstranscriptomicsnormalizationpreprocessingmicroarrayimmunooncologysoftware
7 stars 11.69 score 1.1k scripts 3 dependentsbioc
MAST:Model-based Analysis of Single Cell Transcriptomics
Methods and models for handling zero-inflated single cell assay data.
Maintained by Andrew McDavid. Last updated 5 months ago.
geneexpressiondifferentialexpressiongenesetenrichmentrnaseqtranscriptomicssinglecell
232 stars 11.28 score 1.8k scripts 5 dependents
mages
ChainLadder:Statistical Methods and Models for Claims Reserving in General Insurance
Various statistical methods and models which are typically used for the estimation of outstanding claims reserves in general insurance, including those to estimate the claims development result as required under Solvency II.
Maintained by Markus Gesmann. Last updated 2 months ago.
82 stars 10.04 score 196 scripts 2 dependents
flr
FLCore:Core Package of FLR, Fisheries Modelling in R
Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.
Maintained by Iago Mosqueira. Last updated 10 days ago.
fisheriesflrfisheries-modelling
16 stars 8.78 score 956 scripts 23 dependents
actuaryzhang
cplm:Compound Poisson Linear Models
Likelihood-based and Bayesian methods for various compound Poisson linear models based on Zhang, Yanwei (2013) <doi:10.1007/s11222-012-9343-7>.
Maintained by Yanwei (Wayne) Zhang. Last updated 1 years ago.
16 stars 8.55 score 75 scripts 10 dependents
dkaschek
dMod:Dynamic Modeling and Parameter Estimation in ODE Models
The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.
Maintained by Daniel Kaschek. Last updated 24 days ago.
20 stars 8.35 score 251 scripts
bsaul
geex:An API for M-Estimation
Provides a general, flexible framework for estimating parameters and empirical sandwich variance estimator from a set of unbiased estimating equations (i.e., M-estimation in the vein of Stefanski & Boos (2002) <doi:10.1198/000313002753631330>). All examples from Stefanski & Boos (2002) are published in the corresponding Journal of Statistical Software paper "The Calculus of M-Estimation in R with geex" by Saul & Hudgens (2020) <doi:10.18637/jss.v092.i02>. Also provides an API to compute finite-sample variance corrections.
Maintained by Bradley Saul. Last updated 11 months ago.
asymptoticscovariance-estimatescovariance-estimationestimate-parametersestimating-equationsestimationinferencem-estimationrobustsandwich
8 stars 7.70 score 131 scripts 2 dependents
cran
sn:The Skew-Normal and Related Distributions Such as the Skew-t and the SUN
Build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t and the SUN families. For the skew-normal and the skew-t distributions, statistical methods are provided for data fitting and model diagnostics, in the univariate and the multivariate case.
Maintained by Adelchi Azzalini. Last updated 2 years ago.
3 stars 7.37 score 91 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
quantsulting
ghyp:Generalized Hyperbolic Distribution and Its Special Cases
Detailed functionality for working with the univariate and multivariate Generalized Hyperbolic distribution and its special cases (Hyperbolic (hyp), Normal Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t and Gaussian distribution). Especially, it contains fitting procedures, an AIC-based model selection routine, and functions for the computation of density, quantile, probability, random variates, expected shortfall and some portfolio optimization and plotting routines as well as the likelihood ratio test. In addition, it contains the Generalized Inverse Gaussian distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts. Quantitative risk management: Concepts, techniques and tools. Princeton University Press, Princeton (2005).
Maintained by Marc Weibel. Last updated 7 months ago.
5.55 score 90 scripts 8 dependents
r-forge
fRegression:Rmetrics - Regression Based Decision and Prediction
A collection of functions for linear and non-linear regression modelling. It implements a wrapper for several regression models available in the base and contributed packages of R.
Maintained by Paul J. Northrop. Last updated 10 days ago.
1 stars 5.44 score 23 scripts
staffanbetner
rethinking:Statistical Rethinking book package
Utilities for fitting and comparing models
Maintained by Richard McElreath. Last updated 4 months ago.
5.42 score 4.4k scriptsr-forge
R2MLwiN:Running 'MLwiN' from Within R
An R command interface to the 'MLwiN' multilevel modelling software package.
Maintained by Zhengzheng Zhang. Last updated 11 days ago.
5.35 score 125 scripts
centerforstatistics-ugent
pim:Fit Probabilistic Index Models
Fit a probabilistic index model as described in Thas et al, 2012: <doi:10.1111/j.1467-9868.2011.01020.x>. The interface to the modeling function has changed in this new version. The old version is still available at R-Forge.
Maintained by Joris Meys. Last updated 3 months ago.
10 stars 5.33 score 43 scriptscran
aod:Analysis of Overdispersed Data
Provides a set of functions to analyse overdispersed counts or proportions. Most of the methods are already available elsewhere but are scattered in different packages. The proposed functions should be considered as complements to more sophisticated methods such as generalized estimating equations (GEE) or generalized linear mixed effect models (GLMM).
Maintained by Renaud Lancelot. Last updated 1 years ago.
3 stars 5.15 score 15 dependents
alexzwanenburg
familiar:End-to-End Automated Machine Learning and Model Evaluation
Single unified interface for end-to-end modelling of regression, categorical and time-to-event (survival) outcomes. Models created using familiar are self-containing, and their use does not require additional information such as baseline survival, feature clustering, or feature transformation and normalisation parameters. Model performance, calibration, risk group stratification, (permutation) variable importance, individual conditional expectation, partial dependence, and more, are assessed automatically as part of the evaluation process and exported in tabular format and plotted, and may also be computed manually using export and plot functions. Where possible, metrics and values obtained during the evaluation process come with confidence intervals.
Maintained by Alex Zwanenburg. Last updated 6 months ago.
aiexplainable-aimachine-learningsurvival-analysistabular-data
30 stars 5.03 score 18 scripts
parksw3
fitode:Tools for Ordinary Differential Equations Model Fitting
Methods and functions for fitting ordinary differential equations (ODE) model in 'R'. Sensitivity equations are used to compute the gradients of ODE trajectories with respect to underlying parameters, which in turn allows for more stable fitting. Other fitting methods, such as MCMC (Markov chain Monte Carlo), are also available.
Maintained by Sang Woo Park. Last updated 1 months ago.
6 stars 5.01 score 34 scripts
pchausse
momentfit:Methods of Moments
Several classes for moment-based models are defined. The classes are defined for moment conditions derived from a single equation or a system of equations. The conditions can also be expressed as functions or formulas. Several methods are also offered to facilitate the development of different estimation techniques. The methods that are currently provided are the Generalized method of moments (Hansen 1982; <doi:10.2307/1912775>), for single equations and systems of equation, and the Generalized Empirical Likelihood (Smith 1997; <doi:10.1111/j.0013-0133.1997.174.x>, Kitamura 1997; <doi:10.1214/aos/1069362388>, Newey and Smith 2004; <doi:10.1111/j.1468-0262.2004.00482.x>, and Anatolyev 2005 <doi:10.1111/j.1468-0262.2005.00601.x>).
Maintained by Pierre Chausse. Last updated 1 years ago.
4.80 score 21 scripts 1 dependents
edsandorf
spdesign:Designing Stated Preference Experiments
Contemporary software commonly used to design stated preference experiments are expensive and the code is closed source. This is a free software package with an easy to use interface to make flexible stated preference experimental designs using state-of-the-art methods. For an overview of stated choice experimental design theory, see e.g., Rose, J. M. & Bliemer, M. C. J. (2014) in Hess S. & Daly. A. <doi:10.4337/9781781003152>. The package website can be accessed at <https://spdesign.edsandorf.me>. We acknowledge funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant INSPiRE (Grant agreement ID: 793163).
Maintained by Erlend Dancke Sandorf. Last updated 5 months ago.
4.60 score 20 scripts
datacloning
dcmle:Hierarchical Models Made Easy with Data Cloning
S4 classes around infrastructure provided by the 'coda' and 'dclone' packages to make package development easy as a breeze with data cloning for hierarchical models.
Maintained by Peter Solymos. Last updated 6 months ago.
4.60 score 66 scripts 2 dependents
pi-kappa-devel
markets:Estimation Methods for Markets in Equilibrium and Disequilibrium
Provides estimation methods for markets in equilibrium and disequilibrium. Supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. Also provides post-estimation analysis tools, such as aggregation, marginal effect, and shortage calculations. See Karapanagiotis (2024) <doi:10.18637/jss.v108.i02> for an overview of the functionality and examples. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. Standard errors can be estimated by adjusting for heteroscedasticity or clustering. The equilibrium estimation constitutes a case of a system of linear, simultaneous equations. Instead, the disequilibrium models replace the market-clearing condition with a non-linear, short-side rule and allow for different specifications of price dynamics.
Maintained by Pantelis Karapanagiotis. Last updated 1 years ago.
disequilibriumeconomicsfinancefull-information-maximum-likelihoodmarket-clearingmarket-modelsshort-side-rulecpp
1 stars 4.30 score 9 scriptsbioc
unifiedWMWqPCR:Unified Wilcoxon-Mann Whitney Test for testing differential expression in qPCR data
This packages implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.
Maintained by Joris Meys. Last updated 5 months ago.
differentialexpressiongeneexpressionmicrotitreplateassaymultiplecomparisonqualitycontrolsoftwarevisualizationqpcr
4.18 score
geobosh
pcts:Periodically Correlated and Periodically Integrated Time Series
Classes and methods for modelling and simulation of periodically correlated (PC) and periodically integrated time series. Compute theoretical periodic autocovariances and related properties of PC autoregressive moving average models. Some original methods including Boshnakov & Iqelan (2009) <doi:10.1111/j.1467-9892.2009.00617.x>, Boshnakov (1996) <doi:10.1111/j.1467-9892.1996.tb00281.x>.
Maintained by Georgi N. Boshnakov. Last updated 1 years ago.
par-modelsperiodicperiodic-modelspiar-modelsseasonaltime-seriestime-series-models
3 stars 4.18 score 3 scripts
smac-group
ib:Bias Correction via Iterative Bootstrap
An implementation of the iterative bootstrap procedure of Kuk (1995) <doi:10.1111/j.2517-6161.1995.tb02035.x> to correct the estimation bias of a fitted model object. This procedure has better bias correction properties than the bootstrap bias correction technique.
Maintained by Samuel Orso. Last updated 1 years ago.
2 stars 3.36 score 23 scripts
psolymos
PVAClone:Population Viability Analysis with Data Cloning
Likelihood based population viability analysis in the presence of observation error and missing data. The package can be used to fit, compare, predict, and forecast various growth model types using data cloning.
Maintained by Peter Solymos. Last updated 6 months ago.
1 stars 3.32 score 21 scriptsflr
bbm:FLR Implementation of a Two-Stage Stock Assessment Model
The two-stage biomass-based model for the Bay of Biscay anchovy (Ibaibarriaga et al., 2008).
Maintained by Leire Ibaibarriaga. Last updated 3 years ago.
2.70 score 5 scripts
cran
truncSP:Semi-parametric estimators of truncated regression models
Semi-parametric estimation of truncated linear regression models
Maintained by Anita Lindmark. Last updated 11 years ago.
1.48 score 1 dependents
skoval
blm:Binomial Linear Regression
Implements regression models for binary data on the absolute risk scale. These models are applicable to cohort and population-based case-control data.
Maintained by S.Kovalchik. Last updated 3 years ago.
1.41 score 26 scripts
rvaradhan
anoint:Analysis of Interactions
The tools in this package are intended to help researchers assess multiple treatment-covariate interactions with data from a parallel-group randomized controlled clinical trial. The methods implemented in the package were proposed in Kovalchik, Varadhan and Weiss (2013) <doi: 10.1002/sim.5881>.
Maintained by Ravi Varadhan. Last updated 7 months ago.
1.15 score 14 scripts
apedrods
MAINT.Data:Model and Analyse Interval Data
Implements methodologies for modelling interval data by Normal and Skew-Normal distributions, considering appropriate parameterizations of the variance-covariance matrix that takes into account the intrinsic nature of interval data, and lead to four different possible configuration structures. The Skew-Normal parameters can be estimated by maximum likelihood, while Normal parameters may be estimated by maximum likelihood or robust trimmed maximum likelihood methods.
Maintained by Pedro Duarte Silva. Last updated 2 years ago.
1.15 score 14 scripts