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Simple Key-Value Database
Implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow 'filehash' databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets. Three different file formats for representing the database are currently available and new formats can easily be incorporated by third parties for use in the 'filehash' framework.
Polygons with Holes for the Grammar of Graphics
Tools for working with polygons with holes in 'ggplot2', with a new 'geom' for drawing a 'polypath' applying the 'evenodd' or 'winding' rules.
Analysis of Music and Speech
Analyze music and speech, extract features like MFCCs, handle wave files and their representation in various ways, read mp3, read midi, perform steps of a transcription, ... Also contains functions ported from the 'rastamat' 'Matlab' package.
Mixture Models for Clustering and Classification
An implementation of 14 parsimonious mixture models for model-based clustering or model-based classification. Gaussian, Student's t, generalized hyperbolic, variance-gamma or skew-t mixtures are available. All approaches work with missing data. Celeux and Govaert (1995)
Tools for Single Cell Genomics
A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015)
Parametric Mortality Models, Life Tables and HMD
Fit the most popular human mortality 'laws', and construct
full and abridge life tables given various input indices. A mortality
law is a parametric function that describes the dying-out process of
individuals in a population during a significant portion of their
life spans. For a comprehensive review of the most important mortality
laws see Tabeau (2001)
Normal aka Gaussian 1-d Mixture Models
Onedimensional Normal (i.e. Gaussian) Mixture Models (S3) Classes, for, e.g., density estimation or clustering algorithms research and teaching; providing the widely used Marron-Wand densities. Efficient random number generation and graphics. Fitting to data by efficient ML (Maximum Likelihood) or traditional EM estimation.
Detection of Univariate Outliers
Well known outlier detection techniques in the univariate case. Methods to deal with skewed distribution are included too. The Hidiroglou-Berthelot (1986) method to search for outliers in ratios of historical data is implemented as well. When available, survey weights can be used in outliers detection.
Tools for Working with Posterior Distributions
Provides useful tools for both users and developers of packages
for fitting Bayesian models or working with output from Bayesian models.
The primary goals of the package are to:
(a) Efficiently convert between many different useful formats of
draws (samples) from posterior or prior distributions.
(b) Provide consistent methods for operations commonly performed on draws,
for example, subsetting, binding, or mutating draws.
(c) Provide various summaries of draws in convenient formats.
(d) Provide lightweight implementations of state of the art posterior
inference diagnostics. References: Vehtari et al. (2021)
Fit Structural Equation Models to Multiply Imputed Data
The primary purpose of 'lavaan.mi' is to extend the functionality
of the R package 'lavaan', which implements structural equation modeling
(SEM). When incomplete data have been multiply imputed, the imputed data
sets can be analyzed by 'lavaan' using complete-data estimation methods,
but results must be pooled across imputations (Rubin, 1987,