similar to: draw a function over a histogram

I''m looking for a R function which can maximise this logliklihood function, under the constraits a>0 e b>0 f<-function(param){ a<-param[1] b <-param[2] log(prod)-(a*s2)-(b*s)-n*log(1-((0.5*b/sqrt(a))*(exp((b^2)/(4*a)))*((sqrt(pi ))*(1-pnorm(-b/(2*sqrt(a)), mean=0, sd=1)))))} I''ve tried maxlik constrOptim e donlp2 but without success. Thanks so

i want to plot the histogram and the curve in the same graph.if i have a set of data ,i plot the histogram and also want to see what distribution it was.So i want to plot the curve to know what distribution it like. -- View this message in context: http://www.nabble.com/how-to-plot-the-histogram-and-the-curve-in--the-same-graph-tp20082506p20082506.html Sent from the R help mailing list archive at

Hi, R users: I want to fit my data into a normal distribution by using the command "fitdistr" in "MASS". I changed my data class from "ts" to "numeric" by >class(mydata)="numeric" but after using "fitdistr", I got the result below >fitdistr(mydata,"normal") mean sd NA NA (NA) (NA) the help doc of

Hello, This is a problem for which there seem to be several solutions online, but not really. My question was about plotting a curve over the histogram. All the previous posts and messages talk about generating a *density histogram*using (freq=F) and then plotting the density curve. However, I find that that seriously distorts my data and the plot becomes confounding to the viewer. I was

Dear All, A simple question: packages like fitdistr should be ideal to analyze samples of data taken from a univariate distribution, but what if rather than the raw data of the observations you are given directly and only a histogram? I was thinking about generating artificially a set of data corresponding to the counts binned in the histogram, but this sounds too cumbersome. Another question is

Hi, I am facing the problem that I want to plot a histogram chart set freq to true and overlay with normal or weibull or exponential distribution curve. The sample code is shown as below: >samp<-c(-8.2262,-8.2262,-8.2262,-8.20209,-8.09294,-8.07321,-8.07321, -8.07321,-8.07175,-8.04948,-8.04948,-8.04948,-8.03848,-8.03848,

Dear All: One more thing. I want to add the normal curve to the histogram. Is there away to stretch the peak of the curve to the top of the histogram or at least near to the top of the histogram. Please see the code below. Lizard.tail.lengths <- c(6.2, 6.6, 7.1, 7.4, 7.6, 7.9, 8, 8.3, 8.4, 8.5, 8.6,8.8, 8.8, 9.1, 9.2, 9.4, 9.4, 9.7, 9.9, 10.2, 10.4, 10.8,11.3, 11.9) x<-seq(5,12, 0.001)

Currently, I am doing it this way. x <- mtcars$mpg h<-hist(x, breaks=10, col="red", xlab="Miles Per Gallon", main="Histogram with Normal Curve") xfit<-seq(min(x),max(x),length=40) yfit<-dnorm(xfit,mean=mean(x),sd=sd(x)) yfit <- yfit*diff(h$mids[1:2])*length(x) lines(xfit, yfit, col="blue", lwd=2) But since, ggplot2 has more appealing

Dear List, When I plot a histogram with 'freq=FALSE' and overlay the histogram with a normal pdf curve, everything looks as expected, as follows: x <- rnorm(1000) hist(x, freq=FALSE) curve(dnorm(x), add=TRUE, col="blue") What do I need to do if I want to show the frequencies (freq=TRUE) with the same normal pdf overlay, so that the plot would still look the same? Regards,

Hi R users, I would like to know why these following curve densities don't appear correctly on the histograms. Thank you for your help library(lattice) library(grid) resp <- rnorm(2000) group <- sample(c("G1", "G2", "G3", "G4"), replace = TRUE, size = 1000) histogram(~ resp | group, col="steelblue", panel = function(x, ...){ std

Hi all, I'm using the function "fitdistr" (library MASS) to fit a distribution to given data. What I have to do further, is getting the log-Likelihood-Value from this estimation. Is there any simple possibility to realize it? Regards, Carsten

Hi Abou, Try this: library(plotrix) curve(rescale(dnorm(x ,mean=mean(Lizard.tail.lengths),sd=sd(Lizard.tail.lengths)), c(0,6)),add=TRUE, col=2, lwd = 2) Jim On Mon, Sep 25, 2017 at 9:35 AM, AbouEl-Makarim Aboueissa <abouelmakarim1962 at gmail.com> wrote: > Dear All: > > One more thing. > > I want to add the normal curve to the histogram. Is there away to stretch > the

Hello all, Please consider the following library(lattice) Colors. <-rep(brewer.pal(7, "Dark2"),2) color <- 1 Data.X.. <- data.frame(UnitArea = c(rnorm(1000), rnorm(1000)), Type = c(rep("Base",1000),rep("Log",1000))) histogram( ~ UnitArea | Type, data = Data.X.., xlab = "Unit Area", type = "density", panel =

I would like to add some vertical lines to a lattice plot of histograms. What I am after is a lattice version of abline(v = 1234). The lattice histogram plot is just: histogram( ~ LTSE | approach, data = arrivals) Can anyone point me in the right direction for this? David Scott _________________________________________________________________ David Scott Department of Statistics The

Dear All I would like to draw a picture with the density curve of a normal distribution over a histogram of a set of random numbers extracted from the same normal distribution. Is that possible? Thanks in advance, Paul

Hi all, I'm trying to use the nls function to do a nls curve fit. I have a histogram for my data. I need to get athe best curve fit for this. i am plotting experimental vs the theoretical values. my experimental values are got from my dnorm function, mean=mean of my mid values(hist) and sd=sd of my mid values. For the theoretical i'm using mean and sd of all 20000 raw values as the start

Is there any neat way to add a curve (frequency function or the like) to a histogram or other plots? I haven't found one yet... Robert

Hello, I am a new user of R and found the function dtnorm() in the package msm. My problem now is, that it is not possible for me to get the mean and sd out of a sample when I want a left-truncated normal distribution starting at "0". fitdistr(x,dtnorm, start=list(mean=0, sd=1)) returns the error message "Fehler in "[<-"(`*tmp*`, x >= lower & x <= upper,

Hello All,* *I want to draw a histogram with density curve. * *For that simply i created a data called*"x" *and i used the function called * hist(x, col = "blue", freq = FALSE),** *from this function i got a histogram*. *After that , i tried this function* ** lines(density(x), col = "red", lwd = 2 ) *but i could not get the density curve. So, Again i used

Hi, I thought that I had read somewhere that there was a really simple way to overlay the probability density function of a normal distribution over a histogram, after the histogram has already been plotted. Possibly a one word command. I've found this email from the archives, but I don't think this is what I'm looking for. I thought there was something more simple than