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Tools for Descriptive Statistics
A toolbox for descriptive statistics, based on the computation of frequency and contingency tables. Several statistical functions and plot methods are provided to describe univariate or bivariate distributions of factors, integer series and numerical series either provided as individual values or as bins.
Reliability Diagrams Using Isotonic Regression
Checking the reliability of predictions via the CORP approach,
which generates provably statistically 'C'onsistent, 'O'ptimally binned, and
'R'eproducible reliability diagrams using the 'P'ool-adjacent-violators
algorithm. See Dimitriadis, Gneiting, Jordan (2021)
Tidy Consultant Universe
Loads the 5 packages in the Tidy Consultant Universe. This collection of packages is useful for anyone doing data science, data analysis, or quantitative consulting. The functions in these packages range from data cleaning, data validation, data binning, statistical modeling, and file exporting.
Preprocessor for Data Modeling
Includes binning categorical variables into lesser number of categories based on t-test, converting categorical variables into continuous features using the mean of the response variable for the respective categories, understanding the relationship between the response variable and predictor variables using data transformations.
Probability Functions for Occupancy Distributions
The classical and extended occupancy distributions occur in cases where balls are randomly allocated
to bins. The PDF, CDF, quantile functions, generation of random variates, and calculating
the first four central moments of the distributions are implemented as described in
O’Neill (2019)
Binscatter Estimation and Inference
Provides tools for statistical analysis using the binscatter methods developed by Cattaneo, Crump, Farrell and Feng (2024) < https://nppackages.github.io/references/Cattaneo-Crump-Farrell-Feng_2024_AER.pdf>, Cattaneo, Crump, Farrell and Feng (2025) < https://nppackages.github.io/references/Cattaneo-Crump-Farrell-Feng_2025_Stata.pdf> and Cattaneo, Crump, Farrell and Feng (2026) < https://nppackages.github.io/references/Cattaneo-Crump-Farrell-Feng_2026_RESTAT.pdf>. Binscatter provides a flexible way of describing the relationship between two variables based on partitioning/binning of the independent variable of interest. binsreg(), binsqreg() and binsglm() implement binscatter least squares regression, quantile regression and generalized linear regression respectively, with particular focus on constructing binned scatter plots. They also implement robust (pointwise and uniform) inference of regression functions and derivatives thereof. binstest() implements hypothesis testing procedures for parametric functional forms of and nonparametric shape restrictions on the regression function. binspwc() implements hypothesis testing procedures for pairwise group comparison of binscatter estimators. binsregselect() implements data-driven procedures for selecting the number of bins for binscatter estimation. All the commands allow for covariate adjustment, smoothness restrictions and clustering.
Genetic Algorithm Assisted Genomic Best Liner Unbiased Prediction
Performs genetic algorithm (Scrucca, L (2013)
Infer Cell-Cell Communication from Spatial Transcriptomics
Identifies cell-cell communication hotspots in spatial transcriptomics data using bivariate Local Moran's I statistics on hexagonally binned cells. Provides functions for spatial weighting, ligand-receptor pair filtering, hotspot detection, and visualisation of sender-receiver cell-type interactions.
Lookup for IP Address Proxy Information
A R package to find the IP addresses which are used as VPN anonymizer, open proxies, web proxies and Tor exits. The package lookup the proxy IP address from IP2Proxy BIN Data file. You may visit < https://lite.ip2location.com> for free database download.
Diversity Dynamics using Fossil Sampling Data
Functions to describe sampling and diversity dynamics of fossil occurrence datasets (e.g. from the Paleobiology Database). The package includes methods to calculate range- and occurrence-based metrics of taxonomic richness, extinction and origination rates, along with traditional sampling measures. A powerful subsampling tool is also included that implements frequently used sampling standardization methods in a multiple bin-framework. The plotting of time series and the occurrence data can be simplified by the functions incorporated in the package, as well as other calculations, such as environmental affinities and extinction selectivity testing. Details can be found in: Kocsis, A.T.; Reddin, C.J.; Alroy, J. and Kiessling, W. (2019)