Two solutions not exactly equivalent ; data <- rlnorm(100, meanlog = 1, sdlog = 1) histdata <- hist(data, ylim=c(0, 100)) library(MASS)
f <- fitdistr(data, "lognormal") f$estimate lines(x=seq(from=0, to=50, by=0.1), � y=dlnorm(x=seq(from=0, to=50, by=0.1), meanlog = f$estimate["meanlog"], sdlog = f$estimate["sdlog"])*400 ) library(HelpersMG) m <- modeled.hist(breaks=histdata$breaks, FUN=plnorm, ����������������������������� meanlog = f$estimate["meanlog"], sdlog = f$estimate["sdlog"], sum = 100) points(m$x, m$y, pch=19, col="red") Marc Girondot Le 21/01/2021 � 12:54, Eric Leroy a �crit�: > Hi, > > I would like to plot the histogram of data and fit it with a lognormal > distribution. > > The ideal, would be to superimpose the fit on the histogram and write > the results of the fit on the figure. > > Right now, I was able to plot the histogram and fit the density with a > lognormal, but I can't combine all together. > > Here is the code I wrote : > > histdata <- hist(dataframe$data) > > library(MASS) > > fitdistr(histdata$density, "lognormal") > > Can you help me ? > > Best regards, > > > ______________________________________________ > 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. [[alternative HTML version deleted]] ______________________________________________ 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.
