Package: roll 1.2.2

roll: Rolling and Expanding Statistics

Fast and efficient computation of rolling and expanding statistics for time-series data. The default algorithm in the 'roll' package is an online algorithm that, as observations are added to and removed from a window, updates statistics and discards observations from memory (Welford, 1962, <doi:10.1080/00401706.1962.10490022>; West, 1979, <doi:10.1145/359146.359153>); as a result, the amount of time to evaluate each function is significantly shorter because the computation is independent of the window size. In contrast, an offline algorithm requires all observations in memory to calculate the statistic for each window, so users can trade speed for accuracy and select the offline algorithm by setting the online argument to FALSE. Quantiles are computed from the inverse of the empirical distribution function with averaging at discontinuities (Hyndman and Fan, 1996, <doi:10.1080/00031305.1996.10473566>). Use cases include rolling summary statistics, time-varying relationships between variables, and feature engineering for forecasting and signal construction. The package supports rolling and expanding windows, weights, and handling of missing values via the min_obs, complete_obs, and na_restore arguments. The implementation uses 'RcppParallel' to parallelize the online algorithms across columns and the offline algorithms across windows.

Authors:Jason Foster [aut, cre]

roll_1.2.2.tar.gz
roll_1.2.2.zip(r-4.7-x86_64)roll_1.2.2.zip(r-4.7-arm64)roll_1.2.2.zip(r-4.6-x86_64)roll_1.2.2.zip(r-4.6-arm64)roll_1.2.2.zip(r-4.5-x86_64)
roll_1.2.2.tgz(r-4.6-x86_64)roll_1.2.2.tgz(r-4.6-arm64)roll_1.2.2.tgz(r-4.5-x86_64)roll_1.2.2.tgz(r-4.5-arm64)
roll_1.2.2.tar.gz(r-4.7-arm64)roll_1.2.2.tar.gz(r-4.7-x86_64)roll_1.2.2.tar.gz(r-4.6-arm64)roll_1.2.2.tar.gz(r-4.6-x86_64)
roll_1.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
roll/json (API)

# Install 'roll' in R:
install.packages('roll', repos = c('https://jasonjfoster.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jasonjfoster/roll/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

algorithmsrcppstatisticsopenblascppopenmp

9.30 score 118 stars 10 packages 366 scripts 2.8k downloads 1 mentions 18 exports 3 dependencies

Last updated from:c8197fece6. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK203
linux-devel-x86_64OK201
source / vignettesOK223
linux-release-arm64OK209
linux-release-x86_64OK202
macos-release-arm64OK157
macos-release-x86_64OK431
macos-oldrel-arm64OK172
macos-oldrel-x86_64OK441
windows-devel-arm64OK306
windows-devel-x86_64OK214
windows-release-arm64OK304
windows-release-x86_64OK162
windows-oldrel-x86_64OK202
wasm-releaseOK113

Exports:roll_allroll_anyroll_corroll_covroll_crossprodroll_idxmaxroll_idxminroll_lmroll_maxroll_meanroll_medianroll_minroll_prodroll_quantileroll_scaleroll_sdroll_sumroll_var

Dependencies:RcppRcppArmadilloRcppParallel