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=",")


ggplot(data=tryck, aes(tryck[,1])) +

  geom_histogram(aes(y =..density..),

                 breaks=seq(min(tryck[,1]-1), max(tryck[,1]+1), by = 0.5),



                 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,

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