Created
April 5, 2016 14:57
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Fitting data to a particular distribution
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| suppressMessages(library(fitdistrplus)) | |
| suppressMessages(library(logspline)) | |
| fileInput <- "/Users/hflores/Desktop/datasets/code-benchmarking/output70-t2large.csv" | |
| codebenchmark = read.csv(fileInput, sep=";") | |
| time <- codebenchmark$response | |
| descdist(time, discrete = FALSE) | |
| #weibull | |
| fit.weibull <- fitdist(time, "weibull") | |
| plot(fit.weibull) | |
| fit.weibull$aic | |
| #norm | |
| fit.norm <- fitdist(time, "norm") | |
| plot(fit.norm) | |
| fit.norm$aic | |
| #log normal | |
| fit.lnorm <- fitdist(time, "lnorm") | |
| plot(fit.lnorm) | |
| fit.lnorm$aic | |
| #exponential | |
| fit.exp <- fitdist(time, "exp") | |
| plot(fit.exp) | |
| fit.exp$aic | |
| #gamma | |
| fit.gamma <- fitdist(time, "gamma") | |
| plot(fit.gamma) | |
| fit.gamma$aic |
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