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| # | |
| # lines-per-hour.R, 27 Jul 16 | |
| # | |
| # Data from: | |
| # On the effectiveness of early life cycle defect prediction with Bayesian Nets | |
| # Norman Fenton and Martin Neil and William Marsh and Peter Hearty and {\L}ukasz Radli\'{n}ski and Paul Krause | |
| # | |
| # Example from: | |
| # Empirical Software Engineering using R | |
| # Derek M. Jones | |
| source("ESEUR_config.r") | |
| brew_col=rainbow(3) | |
| loc_hour=read.csv(paste0(ESEUR_dir, "regression/10.1.1.157.6206.csv.xz"), as.is=TRUE) | |
| loc_hour=subset(loc_hour, !is.na(KLoC)) | |
| loc_hour=loc_hour[order(loc_hour$Hours), ] | |
| x_bounds=range(loc_hour$Hours) | |
| y_bounds=range(loc_hour$KLoC) | |
| Hours_KLoC=function(df) | |
| { | |
| plot(df$Hours, df$KLoC, col=point_col, | |
| xlim=x_bounds, ylim=y_bounds, | |
| xlab="Effort (hours)", ylab="Lines of code (Kloc)\n") | |
| lines(loess.smooth(df$Hours, df$KLoC, span=0.4), col=loess_col) | |
| plh_mod=glm(KLoC ~ I(Hours^0.5), data=df) | |
| plh_pred=predict(plh_mod, type="response", se.fit=TRUE) | |
| lines(df$Hours, plh_pred$fit, col=brew_col[1]) | |
| lines(df$Hours, plh_pred$fit+plh_pred$se.fit*1.96, col=brew_col[3]) | |
| lines(df$Hours, plh_pred$fit-plh_pred$se.fit*1.96, col=brew_col[3]) | |
| return(plh_mod) | |
| } | |
| all_mod=Hours_KLoC(loc_hour) | |