GuessCompx: Empirically Estimates Algorithm Complexity

Make an empirical guess on the time and memory complexities of an algorithm or a function. Tests multiple, increasing size random samples of your data and tries to fit various complexity functions o(n), o(n2), o(log(n)), etc. Based on best fit, it predicts the full computation time on your whole dataset. Results are plotted with 'ggplot2'.

Version: 1.0.3
Imports: dplyr, reshape2, ggplot2, lubridate, boot
Suggests: knitr, rmarkdown
Published: 2019-06-03
Author: Marc Agenis and Neeraj Bokde
Maintainer: Marc Agenis <marc.agenis at gmail.com>
BugReports: https://github.com/agenis/GuessCompx/issues
License: GPL-3
URL: https://github.com/agenis/GuessCompx
NeedsCompilation: no
CRAN checks: GuessCompx results

Downloads:

Reference manual: GuessCompx.pdf
Vignettes: Vignette Title
Package source: GuessCompx_1.0.3.tar.gz
Windows binaries: r-devel: GuessCompx_1.0.3.zip, r-devel-gcc8: GuessCompx_1.0.3.zip, r-release: GuessCompx_1.0.3.zip, r-oldrel: GuessCompx_1.0.3.zip
OS X binaries: r-release: GuessCompx_1.0.3.tgz, r-oldrel: GuessCompx_1.0.3.tgz

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