Showing 8 of total 8 results (show query)
mjskay
ggdist:Visualizations of Distributions and Uncertainty
Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.
Maintained by Matthew Kay. Last updated 4 months ago.
ggplot2uncertaintyuncertainty-visualizationvisualizationcpp
859 stars 14.95 score 3.1k scripts 62 dependents
alexanderrobitzsch
TAM:Test Analysis Modules
Includes marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported. For details see Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>, Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>, Formann, 1982 <doi:10.1002/bimj.4710240209>, Formann, 1992 <doi:10.1080/01621459.1992.10475229>.
Maintained by Alexander Robitzsch. Last updated 7 months ago.
item-response-theoryopenblascpp
16 stars 8.93 score 258 scripts 25 dependents
bcallaway11
BMisc:Miscellaneous Functions for Panel Data, Quantiles, and Printing Results
These are miscellaneous functions for working with panel data, quantiles, and printing results. For panel data, the package includes functions for making a panel data balanced (that is, dropping missing individuals that have missing observations in any time period), converting id numbers to row numbers, and to treat repeated cross sections as panel data under the assumption of rank invariance. For quantiles, there are functions to make distribution functions from a set of data points (this is particularly useful when a distribution function is created in several steps), to combine distribution functions based on some external weights, and to invert distribution functions. Finally, there are several other miscellaneous functions for obtaining weighted means, weighted distribution functions, and weighted quantiles; to generate summary statistics and their differences for two groups; and to add or drop covariates from formulas.
Maintained by Brantly Callaway. Last updated 2 months ago.
7 stars 7.92 score 110 scripts 8 dependents
hughparsonage
hutils:Miscellaneous R Functions and Aliases
Provides utility functions for, and drawing on, the 'data.table' package. The package also collates useful miscellaneous functions extending base R not available elsewhere. The name is a portmanteau of 'utils' and the author.
Maintained by Hugh Parsonage. Last updated 2 years ago.
12 stars 7.76 score 219 scripts 8 dependents
mayer79
MetricsWeighted:Weighted Metrics and Performance Measures for Machine Learning
Provides weighted versions of several metrics and performance measures used in machine learning, including average unit deviances of the Bernoulli, Tweedie, Poisson, and Gamma distributions, see Jorgensen B. (1997, ISBN: 978-0412997112). The package also contains a weighted version of generalized R-squared, see e.g. Cohen, J. et al. (2002, ISBN: 978-0805822236). Furthermore, 'dplyr' chains are supported.
Maintained by Michael Mayer. Last updated 8 months ago.
machine-learningmetricsperformancestatistics
11 stars 6.79 score 75 scripts 5 dependents
tobiasschoch
robsurvey:Robust Survey Statistics Estimation
Robust (outlier-resistant) estimators of finite population characteristics like of means, totals, ratios, regression, etc. Available methods are M- and GM-estimators of regression, weight reduction, trimming, and winsorization. The package extends the 'survey' <https://CRAN.R-project.org/package=survey> package.
Maintained by Tobias Schoch. Last updated 4 months ago.
9 stars 6.16 score 5 scripts
helske
diagis:Diagnostic Plot and Multivariate Summary Statistics of Weighted Samples from Importance Sampling
Fast functions for effective sample size, weighted multivariate mean, variance, and quantile computation, and weight diagnostic plot for generic importance sampling type or other probability weighted samples.
Maintained by Jouni Helske. Last updated 2 years ago.
cppimportance-samplingweighted-samplesopenblascpp
1 stars 4.32 score 14 scripts 1 dependents
ashesitr
reservr:Fit Distributions and Neural Networks to Censored and Truncated Data
Define distribution families and fit them to interval-censored and interval-truncated data, where the truncation bounds may depend on the individual observation. The defined distributions feature density, probability, sampling and fitting methods as well as efficient implementations of the log-density log f(x) and log-probability log P(x0 <= X <= x1) for use in 'TensorFlow' neural networks via the 'tensorflow' package. Allows training parametric neural networks on interval-censored and interval-truncated data with flexible parameterization. Applications include Claims Development in Non-Life Insurance, e.g. modelling reporting delay distributions from incomplete data, see Bücher, Rosenstock (2022) <doi:10.1007/s13385-022-00314-4>.
Maintained by Alexander Rosenstock. Last updated 9 months ago.
4 stars 3.78 score 9 scripts