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poissonconsulting
nlist:Lists of Numeric Atomic Objects
Create and manipulate numeric list ('nlist') objects. An 'nlist' is an S3 list of uniquely named numeric objects. An numeric object is an integer or double vector, matrix or array. An 'nlists' object is a S3 class list of 'nlist' objects with the same names, dimensionalities and typeofs. Numeric list objects are of interest because they are the raw data inputs for analytic engines such as 'JAGS', 'STAN' and 'TMB'. Numeric lists objects, which are useful for storing multiple realizations of of simulated data sets, can be converted to coda::mcmc and coda::mcmc.list objects.
Maintained by Joe Thorley. Last updated 2 months ago.
139.4 match 6 stars 7.23 score 13 scripts 12 dependentspoissonconsulting
mcmcr:Manipulate MCMC Samples
Functions and classes to store, manipulate and summarise Monte Carlo Markov Chain (MCMC) samples. For more information see Brooks et al. (2011) <isbn:978-1-4200-7941-8>.
Maintained by Joe Thorley. Last updated 2 months ago.
10.8 match 17 stars 7.66 score 111 scripts 10 dependents
stan-dev
rstan:R Interface to Stan
User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Maintained by Ben Goodrich. Last updated 1 days ago.
bayesian-data-analysisbayesian-inferencebayesian-statisticsmcmcstancpp
3.3 match 1.1k stars 18.67 score 14k scripts 279 dependentsstan-dev
loo:Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models
Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo, as described in Vehtari, Gelman, and Gabry (2017) <doi:10.1007/s11222-016-9696-4>. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.
Maintained by Jonah Gabry. Last updated 1 days ago.
bayesbayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-statisticscross-validationinformation-criterionmodel-comparisonstan
3.3 match 152 stars 17.30 score 2.6k scripts 297 dependents
paulponcet
bazar:Miscellaneous Basic Functions
A collection of miscellaneous functions for copying objects to the clipboard ('Copy'); manipulating strings ('concat', 'mgsub', 'trim', 'verlan'); loading or showing packages ('library_with_dep', 'require_with_dep', 'sessionPackages'); creating or testing for named lists ('nlist', 'as_nlist', 'is_nlist'), formulas ('is_formula'), empty objects ('as_empty', 'is_empty'), whole numbers ('as_wholenumber', 'is_wholenumber'); testing for equality ('almost_equal', 'almost_zero') and computing uniqueness ('almost_unique'); getting modified versions of usual functions ('rle2', 'sumNA'); making a pause or a stop ('pause', 'stopif'); converting into a function ('as_fun'); providing a C like ternary operator ('condition %?% true %:% false'); finding packages and functions ('get_all_pkgs', 'get_all_funs'); and others ('erase', '%nin%', 'unwhich', 'top', 'bot', 'normalize').
Maintained by Paul Poncet. Last updated 6 years ago.
9.8 match 1 stars 4.46 score 79 scripts 2 dependents
canmod
macpan2:Fast and Flexible Compartmental Modelling
Fast and flexible compartmental modelling with Template Model Builder.
Maintained by Steve Walker. Last updated 15 hours ago.
compartmental-modelsepidemiologyforecastingmixed-effectsmodel-fittingoptimizationsimulationsimulation-modelingcpp
3.3 match 4 stars 8.89 score 246 scripts 1 dependentspoissonconsulting
sims:Simulate Data from R or 'JAGS' Code
Generates data from R or 'JAGS' code for use in simulation studies. The data are returned as an 'nlist::nlists' object and/or saved to file as individual '.rds' files. Parallelization is implemented using the 'future' package. Progress is reported using the 'progressr' package.
Maintained by Audrey Beliveau. Last updated 2 months ago.
5.4 match 5.38 score 6 scripts
bioc
GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor
If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.
Maintained by Kristyna Kupkova. Last updated 5 months ago.
softwaregenomeannotationgenomeassemblydatarepresentationsequencingcoveragefunctionalgenomicsvisualization
3.3 match 26 stars 7.44 score 25 scripts
krlmlr
kimisc:Kirill's Miscellaneous Functions
A collection of useful functions not found anywhere else, mainly for programming: Pretty intervals, generalized lagged differences, checking containment in an interval, and an alternative interface to assign().
Maintained by Kirill Müller. Last updated 3 months ago.
3.3 match 18 stars 6.47 score 76 scripts 3 dependentscanmod
iidda:Processing Infectious Disease Datasets in IIDDA.
Part of an open toolchain for processing infectious disease datasets available through the IIDDA data repository.
Maintained by Steve Walker. Last updated 4 months ago.
3.3 match 6.07 score 133 scripts 3 dependents
skranz
RTutor:Interactive R problem sets with automatic testing of solutions and automatic hints
Interactive R problem sets with automatic testing of solutions and automatic hints
Maintained by Sebastian Kranz. Last updated 1 years ago.
economicslearn-to-codeproblem-setrstudiortutorshinyteaching
3.3 match 205 stars 5.83 score 111 scripts 1 dependentsskranz
gtree:gtree basic functionality to model and solve games
gtree basic functionality to model and solve games
Maintained by Sebastian Kranz. Last updated 4 years ago.
economic-experimentseconomicsgambitgame-theorynash-equilibrium
3.3 match 18 stars 3.79 score 23 scripts 1 dependentsskranz
RelationalContracts:Characterize relational contracts in repated or stochastic games
Characterize relational contracts in repated or stochastic games. Can also analyse repeated negotiation equilibria.
Maintained by Sebastian Kranz. Last updated 4 years ago.
dynamic-gameeconomicsgame-theoryhold-upnash-equilibriumrepeated-gamestochastic-game
3.3 match 4 stars 2.48 score 15 scriptsskranz
sktools:Helpful functions used in my courses
Several helpful functions that I use in my courses
Maintained by Sebastian Kranz. Last updated 4 years ago.
3.3 match 1 stars 2.15 score 28 scriptsskranz
rmdtools:Tools for RMarkdown
Tools for RMarkdown
Maintained by Sebastian Kranz. Last updated 4 years ago.
3.3 match 1 stars 1.78 score 6 scripts 2 dependentsskranz
shinyEventsUI:Some shiny widgets that only work with shinyEvents
Some shiny widgets that only work with shinyEvents
Maintained by Sebastian Kranz. Last updated 4 years ago.
3.3 match 1 stars 1.70 scoreskranz
MetaStudies:Shiny app and function for Meta studies following Andrews and Kasy (2019).
This package mainly consists of Maximilan Kasy's code of his shiny app for MetaStudies on publication bias. I added some stuff, rewrote it a bit and put everything into an R package. The original code is here: https://github.com/maxkasy/MetaStudiesApp The code is based on Andrews and Kasy (2019). In particular, I added code to run misspecification tests that will be explained in Kranz and Pütz (2021). References: - Andrews, Isaiah and Maximilian Kasy. 2019. “Identification of and correction for publication bias.” American Economic Review 109 (8): 2766-94. - Kranz, Sebastian and Peter Pütz. 2021 “Rounding and other pitfalls in meta-studies on p-hacking and publication bias. A comment on Brodeur et al. (2020)”, working paper.
Maintained by Sebastian Kranz. Last updated 4 years ago.
3.3 match 1.70 score 5 scriptspoissonconsulting
universals:S3 Generics for Bayesian Analyses
Provides S3 generic methods and some default implementations for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples. The purpose of 'universals' is to reduce package dependencies and conflicts. The 'nlist' package implements many of the methods for its 'nlist' class.
Maintained by Joe Thorley. Last updated 2 months ago.
0.8 match 4 stars 6.37 score 1 scripts 20 dependentsskranz
shinyEventsLogin:A simple login framework as part of shinyEvents apps (probably not very secure)
A simple login framework for shinyEvents apps (probably not very secure)
Maintained by Sebastian Kranz. Last updated 9 months ago.
3.3 match 1 stars 1.00 scoreskranz
skUtils:Helper functions for repgames and dyngames
Helper functions needed by my package repgames and dyngames
Maintained by Sebastian Kranz. Last updated 4 years ago.
3.3 match 1.00 score