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Create Compact Hash Digests of R Objects
Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', 'xxhash', 'murmurhash', 'spookyhash', 'blake3', 'crc32c', 'xxh3_64', and 'xxh3_128' algorithms) permitting easy comparison of R language objects, as well as functions such as 'hmac()' to create hash-based message authentication code. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as 'OpenSSL' should be used.
Polygon Clipping
R port of Angus Johnson's open source library 'Clipper'. Performs polygon clipping operations (intersection, union, set minus, set difference) for polygonal regions of arbitrary complexity, including holes. Computes offset polygons (spatial buffer zones, morphological dilations, Minkowski dilations) for polygonal regions and polygonal lines. Computes Minkowski Sum of general polygons. There is a function for removing self-intersections from polygon data.
Convert, Validate, Format and Print Geographic Coordinates and Waypoints
Convert, validate, format and elegantly print geographic coordinates and waypoints (paired latitude and longitude values) in decimal degrees, degrees and minutes, and degrees, minutes and seconds using high performance C++ code to enable rapid conversion and formatting of large coordinate and waypoint datasets.
Extensible, Parallelizable Implementation of the Random Forest Algorithm
Scalable implementation of classification and regression forests, as described by Breiman (2001),
Targeted Maximum Likelihood Estimation
Targeted maximum likelihood estimation of point treatment effects (Targeted Maximum Likelihood Learning, The International Journal of Biostatistics, 2(1), 2006. This version automatically estimates the additive treatment effect among the treated (ATT) and among the controls (ATC). The tmle() function calculates the adjusted marginal difference in mean outcome associated with a binary point treatment, for continuous or binary outcomes. Relative risk and odds ratio estimates are also reported for binary outcomes. Missingness in the outcome is allowed, but not in treatment assignment or baseline covariate values. The population mean is calculated when there is missingness, and no variation in the treatment assignment. The tmleMSM() function estimates the parameters of a marginal structural model for a binary point treatment effect. Effect estimation stratified by a binary mediating variable is also available. An ID argument can be used to identify repeated measures. Default settings call 'SuperLearner' to estimate the Q and g portions of the likelihood, unless values or a user-supplied regression function are passed in as arguments.
Mark-Recapture Distance Sampling
Animal abundance estimation via conventional, multiple covariate and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator.
Generate New Multivariate Normal Samples from Permutations
Given a vector of multivariate normal data, a matrix of covariates and the data covariance matrix, generate new multivariate normal samples that have the same covariance matrix based on permutations of the transformed data residuals.
Process GPX Files into R Data Structures
Process open standard GPX files into data.frames for further use and analysis in R.
Companion to the Forthcoming Book - R you Ready?
Package contains some data and functions that are used in my forthcoming "R you ready?" book.
Download Data from the NISRA Data Portal
Download data from the Northern Ireland Statistics and Research Agency (NISRA) data portal, accessed at < https://data.nisra.gov.uk>. NISRA is a government agency and the principal source of official statistics and social research on Northern Ireland.