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'.


Reference manual

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1.0.3 by Marc Agenis, 2 years ago


Report a bug at https://github.com/agenis/GuessCompx/issues

Browse source code at https://github.com/cran/GuessCompx

Authors: Marc Agenis <[email protected]> and Neeraj Bokde <[email protected]>

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, reshape2, ggplot2, lubridate, boot

Suggests knitr, rmarkdown

See at CRAN