Fitting a normal distribution in R

Question

I'm using the following code to fit the normal distribution. The link for the dataset for "b" (too large to post directly) is :

link for b

setwd("xxxxxx")
library(fitdistrplus)

require(MASS)
tazur <-read.csv("b", header= TRUE, sep=",")
claims<-tazur$b
a<-log(claims)
plot(hist(a))

After plotting the histogram, it seems a normal distribution should fit well.

f1n <- fitdistr(claims,"normal")
summary(f1n)

#Length Class  Mode   
#estimate 2      -none- numeric
#sd       2      -none- numeric
#vcov     4      -none- numeric
#n        1      -none- numeric
#loglik   1      -none- numeric

plot(f1n)

But when I try to plot the fitted distribution, I get

Error in xy.coords(x, y, xlabel, ylabel, log) : 

  'x' is a list, but does not have components 'x' and 'y'

and even the summary statistics are off for f1n.

Any ideas?

Answer 1

Looks like you are making confusion between MASS::fitdistr and fitdistrplus::fitdist.

• MASS::fitdistr returns object of class "fitdistr", and there is no plot method for this. So you need to extract estimated parameters and plot the estimated density curve yourself.
• I don't know why you load package fitdistrplus, because your function call clearly shows you are using MASS. Anyway, fitdistrplus has function fitdist which returns object of class "fitdist". There is plot method for this class, but it won't work for "fitdistr" returned by MASS.

I will show you how to work with both packages.

## reproducible example
set.seed(0); x <- rnorm(500)

---

Using MASS::fitdistr

No plot method is available, so do it ourselves.

library(MASS)
fit <- fitdistr(x, "normal")
class(fit)
# [1] "fitdistr"

para <- fit$estimate
#         mean            sd 
#-0.0002000485  0.9886248515 

hist(x, prob = TRUE)
curve(dnorm(x, para[1], para[2]), col = 2, add = TRUE)

---

Using fitdistrplus::fitdist

library(fitdistrplus)
FIT <- fitdist(x, "norm")    ## note: it is "norm" not "normal"
class(FIT)
# [1] "fitdist"

plot(FIT)    ## use method `plot.fitdist`