Hi, I do not know how to post in general again, however my csv contains around 5-250k data Points depending on vehicle/road type and pressure exerted on geotechnical structures. I have used R to develope histograms of said csv files and will attach such Picture to you in this mail and the csv used. Below I will type the R code I have used for this histogram.
------------------------------------------------------------ ---------------------------- tryck <- read.csv("radmanso_2017.csv", sep=";", dec=",") ##### H??R KOLLAR VI ALLA DATA PUNKTER ###### ggplot(data=tryck, aes(tryck[,1])) + geom_histogram(aes(y =..density..), breaks=seq(min(tryck[,1]-1), max(tryck[,1]+1), by = 0.5), col="black", fill="green", alpha = .2) + geom_density(col=2) + labs(title="Pressure for rådmansö") + labs(x="Pressure [kPa]", y="Amount of vehicles (Percentage)")+ stat_function(fun=dnorm, colour="blue", args = list(mean = mean(tryck[,1]), sd = sd(tryck[,1]))) My problem now is to find a statistical distribution that corresponds well with my histograms with the use of Visual aids, cumulative distributions or goodness of fit tests which I can’t develope a code for as my csv wont get called forth and I do not know how to proceed from that Point on to develop such an aid. If you have any input on how to read the csv file and call forth a distribution to try on my data points such as Weibull, beta, chi or gen. Extreme value distributions I would much appreciate the help! Kind regards, Mohammad
______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.