Fitting a density curve to a histogram in R

curve-fitting, histogram, r, r-faq

Solution

If I understand your question correctly, then you probably want a density estimate along with the histogram:

X <- c(rep(65, times=5), rep(25, times=5), rep(35, times=10), rep(45, times=4))
hist(X, prob=TRUE)            # prob=TRUE for probabilities not counts
lines(density(X))             # add a density estimate with defaults
lines(density(X, adjust=2), lty="dotted")   # add another "smoother" density

Edit a long while later:

Here is a slightly more dressed-up version:

X <- c(rep(65, times=5), rep(25, times=5), rep(35, times=10), rep(45, times=4))
hist(X, prob=TRUE, col="grey")# prob=TRUE for probabilities not counts
lines(density(X), col="blue", lwd=2) # add a density estimate with defaults
lines(density(X, adjust=2), lty="dotted", col="darkgreen", lwd=2)

along with the graph it produces:

Problem

Is there a function in R that fits a curve to a histogram? Let's say you had the following histogram ``` hist(c(rep(65, times=5), rep(25, times=5), rep(35, times=10), rep(45, times=4))) ``` It looks normal, but it's skewed. I want to fit a normal curve that is skewed to wrap around this histogram. This question is rather basic, but I can't seem to find the answer for R on the internet.

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