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 |
| 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-release: GuessCompx_1.0.3.zip, r-oldrel: GuessCompx_1.0.3.zip |
| macOS binaries: | r-release: GuessCompx_1.0.3.tgz, r-oldrel: GuessCompx_1.0.3.tgz |
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