R Package Scholar
27,073
Referenced by ⇅ Year
BartMixVs: Variable Selection Using Bayesian Additive Regression Trees (Version 1.0.0)

2022
bayesbr: Beta Regression on a Bayesian Model (Version 0.0.1.0)

2020
SPQR: Semi-Parametric Quantile Regression (Version 0.1.0)

2022
expertsurv: Incorporate Expert Opinion with Parametric Survival Models (Version 1.3.0)

2023
publipha: Bayesian Meta-Analysis with Publications Bias and P-Hacking (Version 0.1.2)

2020
BAMBI: Bivariate Angular Mixture Models (Version 2.3.6)

2017
BayesGrowth: Estimate Fish Growth Using MCMC Analysis (Version 1.0.0)

2023
EBcoBART: Co-Data Learning for Bayesian Additive Regression Trees (Version 1.1.0)

2024
FlexReg: Regression Models for Bounded Continuous and Discrete Responses (Version 1.3.0)

2020
GUD: Bayesian Modal Regression Based on the GUD Family (Version 1.0.2)

2024
LMMELSM: Fit Latent Multivariate Mixed Effects Location Scale Models (Version 0.2.0)

2021
MetaStan: Bayesian Meta-Analysis via 'Stan' (Version 1.0.0)

2018
MixSIAR: Bayesian Mixing Models in R (Version 3.1.12)

2016
StanMoMo: Bayesian Mortality Modelling with 'Stan' (Version 1.2.0)

2021
TriDimRegression: Bayesian Statistics for 2D/3D Transformations (Version 1.0.2)

2021
bayclumpr: Bayesian Analysis of Clumped Isotope Datasets (Version 0.1.0)

2023
bayesGAM: Fit Multivariate Response Generalized Additive Models using Hamiltonian Monte Carlo (Version 0.0.2)

2020
bayesdfa: Bayesian Dynamic Factor Analysis (DFA) with 'Stan' (Version 1.3.3)

2018
bayesforecast: Bayesian Time Series Modeling with Stan (Version 1.0.1)

2021
bayesnec: A Bayesian No-Effect- Concentration (NEC) Algorithm (Version 2.1.3.0)

2021
bayesplot: Plotting for Bayesian Models (Version 1.11.1)

2016
bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan' (Version 0.8.5)

2019
beanz: Bayesian Analysis of Heterogeneous Treatment Effect (Version 3.1)

2016
bellreg: Count Regression Models Based on the Bell Distribution (Version 0.0.2.2)

2020
bistablehistory: Cumulative History Analysis for Bistable Perception Time Series (Version 1.1.2)

2021
blavaan: Bayesian Latent Variable Analysis (Version 0.5-6)

2015
bmgarch: Bayesian Multivariate GARCH Models (Version 2.0.0)

2020
bmggum: Bayesian Multidimensional Generalized Graded Unfolding Model (Version 0.1.0)

2021
bmscstan: Bayesian Multilevel Single Case Models using 'Stan' (Version 1.2.1.0)

2020
bmstdr: Bayesian Modeling of Spatio-Temporal Data with R (Version 0.7.9)

2022
brms: Bayesian Regression Models using 'Stan' (Version 2.22.0)

2015
bsitar: Bayesian Super Imposition by Translation and Rotation Growth Curve Analysis (Version 0.2.1)

2023
causalOT: Optimal Transport Weights for Causal Inference (Version 1.0.2)

2022
conformalbayes: Jackknife(+) Predictive Intervals for Bayesian Models (Version 0.1.2)

2022
disbayes: Bayesian Multi-State Modelling of Chronic Disease Burden Data (Version 1.1.0)

2022
dynamite: Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data (Version 1.5.2)

2022
eDNAjoint: Joint Modeling of Traditional and Environmental DNA Survey Data in a Bayesian Framework (Version 0.2)

2024
evidence: Analysis of Scientific Evidence Using Bayesian and Likelihood Methods (Version 0.8.10)

2018
flocker: Flexible Occupancy Estimation with Stan (Version 1.0-0)

2024
footBayes: Fitting Bayesian and MLE Football Models (Version 0.2.0)

2022
glmmfields: Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling (Version 0.1.8)

2018
hBayesDM: Hierarchical Bayesian Modeling of Decision-Making Tasks (Version 1.2.1)

2016
hbamr: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan' (Version 2.3.2)

2023
hsstan: Hierarchical Shrinkage Stan Models for Biomarker Selection (Version 0.8.2)

2019
mcmcsae: Markov Chain Monte Carlo Small Area Estimation (Version 0.7.7)

2020
mcp: Regression with Multiple Change Points (Version 0.3.4)

2020
measr: Bayesian Psychometric Measurement Using 'Stan' (Version 1.0.0)

2023
missingHE: Missing Outcome Data in Health Economic Evaluation (Version 1.5.0)

2019
multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data (Version 1.3.0.2)

2023
multinma: Bayesian Network Meta-Analysis of Individual and Aggregate Data (Version 0.7.2)

2020
mvgam: Multivariate (Dynamic) Generalized Additive Models (Version 1.1.3)

2024
pcFactorStan: Stan Models for the Paired Comparison Factor Model (Version 1.5.4)

2019
performance: Assessment of Regression Models Performance (Version 0.12.4)

2019
phylopairs: Comparative Analyses of Lineage-Pair Traits (Version 0.1.0)

2024
projpred: Projection Predictive Feature Selection (Version 2.8.0)

2018
rPBK: Inference and Prediction of Generic Physiologically-Based Kinetic Models (Version 0.2.4)

2022
rater: Statistical Models of Repeated Categorical Rating Data (Version 1.3.1)

2020
rbioacc: Inference and Prediction of ToxicoKinetic (TK) Models (Version 1.2.1)

2021
redist: Simulation Methods for Legislative Redistricting (Version 4.2.0)

2015
rmsb: Bayesian Regression Modeling Strategies (Version 1.1-1)

2020
rmstBayespara: Bayesian Restricted Mean Survival Time for Cluster Effect (Version 0.1.0)

2024
rstan: R Interface to Stan (Version 2.32.6)

2015
rstanarm: Bayesian Applied Regression Modeling via Stan (Version 2.32.1)

2016
rtmpt: Fitting (Exponential/Diffusion) RT-MPT Models (Version 2.0-1)

2019
spsurv: Bernstein Polynomial Based Semiparametric Survival Analysis (Version 1.0.0)

2020
tipsae: Tools for Handling Indices and Proportions in Small Area Estimation (Version 1.0.3)

2022
ubms: Bayesian Models for Data from Unmarked Animals using 'Stan' (Version 1.2.7)

2021
walker: Bayesian Generalized Linear Models with Time-Varying Coefficients (Version 1.0.10)

2017
webSDM: Including Known Interactions in Species Distribution Models (Version 1.1-5)

2022

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.

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