Showing 12 of total 12 results (show query)
sebkrantz
collapse:Advanced and Fast Data Transformation
A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated with base R classes, 'dplyr'/'tibble', 'data.table', 'sf', 'units', 'plm' (panel-series and data frames), and 'xts'/'zoo'.
Maintained by Sebastian Krantz. Last updated 8 days ago.
data-aggregationdata-analysisdata-manipulationdata-processingdata-sciencedata-transformationeconometricshigh-performancepanel-datascientific-computingstatisticstime-seriesweightedweightscppopenmp
672 stars 16.68 score 708 scripts 99 dependents
asgr
imager:Image Processing Library Based on 'CImg'
Fast image processing for images in up to 4 dimensions (two spatial dimensions, one time/depth dimension, one colour dimension). Provides most traditional image processing tools (filtering, morphology, transformations, etc.) as well as various functions for easily analysing image data using R. The package wraps 'CImg', <http://cimg.eu>, a simple, modern C++ library for image processing.
Maintained by Aaron Robotham. Last updated 6 days ago.
17 stars 13.53 score 2.4k scripts 44 dependents
edwinth
padr:Quickly Get Datetime Data Ready for Analysis
Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).
Maintained by Edwin Thoen. Last updated 4 months ago.
132 stars 11.55 score 428 scripts 20 dependents
gjmvanboxtel
gsignal:Signal Processing
R implementation of the 'Octave' package 'signal', containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing.
Maintained by Geert van Boxtel. Last updated 2 months ago.
24 stars 10.07 score 133 scripts 34 dependents
robinhankin
emulator:Bayesian Emulation of Computer Programs
Allows one to estimate the output of a computer program, as a function of the input parameters, without actually running it. The computer program is assumed to be a Gaussian process, whose parameters are estimated using Bayesian techniques that give a PDF of expected program output. This PDF is conditional on a training set of runs, each consisting of a point in parameter space and the model output at that point. The emphasis is on complex codes that take weeks or months to run, and that have a large number of undetermined input parameters; many climate prediction models fall into this class. The emulator essentially determines Bayesian posterior estimates of the PDF of the output of a model, conditioned on results from previous runs and a user-specified prior linear model. The package includes functionality to evaluate quadratic forms efficiently.
Maintained by Robin K. S. Hankin. Last updated 9 months ago.
4 stars 8.27 score 56 scripts 17 dependents
jaryan
mmap:Map Pages of Memory
R interface to POSIX mmap and Window's MapViewOfFile.
Maintained by Jeffrey A. Ryan. Last updated 1 years ago.
14 stars 7.40 score 44 scripts 3 dependents
geobosh
gbutils:Utilities for Simulation, Plots, Quantile Functions and Programming
Plot density and distribution functions with automatic selection of suitable regions. Numerically invert (compute quantiles) distribution functions. Simulate real and complex numbers from distributions of their magnitude and arguments. Optionally, the magnitudes and/or arguments may be fixed in almost arbitrary ways. Create polynomials from roots given in Cartesian or polar form. Small programming utilities: check if an object is identical to NA, count positional arguments in a call, set intersection of more than two sets, check if an argument is unnamed, compute the graph of S4 classes in packages.
Maintained by Georgi N. Boshnakov. Last updated 3 years ago.
adjacency-matrixcomplex-numbersplotting-functionss4s4classsimulation
1 stars 7.32 score 29 scripts 56 dependents
trinker
qdapTools:Tools for the 'qdap' Package
A collection of tools associated with the 'qdap' package that may be useful outside of the context of text analysis.
Maintained by Tyler Rinker. Last updated 2 years ago.
16 stars 6.96 score 408 scripts 5 dependents
dpmcsuss
iGraphMatch:Tools for Graph Matching
Versatile tools and data for graph matching analysis with various forms of prior information that supports working with 'igraph' objects, matrix objects, or lists of either.
Maintained by Daniel Sussman. Last updated 11 months ago.
graph-algorithmsgraph-matchingcpp
9 stars 5.65 score 9 scripts
s6sebusc
dualtrees:Decimated and Undecimated 2D Complex Dual-Tree Wavelet Transform
An implementation of the decimated two-dimensional complex dual-tree wavelet transform as described in Kingsbury (1999) <doi:10.1098/rsta.1999.0447> and Selesnick et al. (2005) <doi:10.1109/MSP.2005.1550194>. Also includes the undecimated version and spectral bias correction described in Nelson et al. (2018) <doi:10.1007/s11222-017-9784-0>. The code is partly based on the 'dtcwt' Python library.
Maintained by Sebastian Buschow. Last updated 1 years ago.
3.18 score 1 dependents
cran
astrochron:A Computational Tool for Astrochronology
Routines for astrochronologic testing, astronomical time scale construction, and time series analysis <doi:10.1016/j.earscirev.2018.11.015>. Also included are a range of statistical analysis and modeling routines that are relevant to time scale development and paleoclimate analysis.
Maintained by Stephen Meyers. Last updated 6 months ago.
5 stars 2.70 score