Interface to Unidata netCDF (Version 4 or Earlier) Format Data Files

Provides a high-level R interface to data files written using Unidata's netCDF library (version 4 or earlier), which are binary data files that are portable across platforms and include metadata information in addition to the data sets. Using this package, netCDF files (either version 4 or "classic" version 3) can be opened and data sets read in easily. It is also easy to create new netCDF dimensions, variables, and files, in either version 3 or 4 format, and manipulate existing netCDF files. This package replaces the former ncdf package, which only worked with netcdf version 3 files. For various reasons the names of the functions have had to be changed from the names in the ncdf package. The old ncdf package is still available at the URL given below, if you need to have backward compatibility. It should be possible to have both the ncdf and ncdf4 packages installed simultaneously without a problem. However, the ncdf package does not provide an interface for netcdf version 4 files.

Manipulating Labelled Data

Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.

Automatically Position Non-Overlapping Text Labels with 'ggplot2'

Provides text and label geoms for 'ggplot2' that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.

Help to Fit of a Parametric Distribution to Non-Censored or Censored Data

Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.

Official R API for Fetching Data from 'EODHD'

Second and backward-incompatible version of R package 'eodhd' < https://eodhd.com/>, extended with a cache and quota system, also offering functions for cleaning and aggregating the financial data.

World Map Data from Natural Earth

Facilitates mapping by making natural earth map data from < https://www.naturalearthdata.com/> more easily available to R users.

Tidy Temporal Data Frames and Tools

Provides a 'tbl_ts' class (the 'tsibble') for temporal data in an data- and model-oriented format. The 'tsibble' provides tools to easily manipulate and analyse temporal data, such as filling in time gaps and aggregating over calendar periods.

Interface with 'Nominatim' API Service

Lite interface for getting data from 'OSM' service 'Nominatim' < https://nominatim.org/release-docs/latest/>. Extract coordinates from addresses, find places near a set of coordinates and return spatial objects on 'sf' format.

A Fast Implementation of Random Forests

A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.

Manipulation of Linear Systems of (in)Equalities

Variable elimination (Gaussian elimination, Fourier-Motzkin elimination), Moore-Penrose pseudoinverse, reduction to reduced row echelon form, value substitution, projecting a vector on the convex polytope described by a system of (in)equations, simplify systems by removing spurious columns and rows and collapse implied equalities, test if a matrix is totally unimodular, compute variable ranges implied by linear (in)equalities.