no_one - 1 year ago 72

R Question

I need to do exactly what @interstellar asked here Fit poisson distribution to data but within the R environment (not matlab).

So, I created a barplot with my observed values and I just need to fit a poisson distribution on it.

Here my data:

`df = read.table(text = 'Var1 Freq`

6 1

7 2

8 5

9 7

10 9

11 6

12 4

13 3

14 2

15 1', header = TRUE)

the barplot created is the following:

`t = barplot(df$Freq, ylim = c(0,10))`

axis(1, at=t, labels=df$Var1)

I am still new to R so how I could use the

`fitdist`

Any help would be really appreciated.

UPDATE

I have worked out something but I am not sure 100% if it is correct:

`#create barplot`

t = barplot(df$Freq, ylim = c(0,10))

axis(1, at=t, labels=df$Var1)

#find lambda value from my data

pois = fitdist(df$Freq, 'pois', method = 'mle')

print(pois)

#result

Fitting of the distribution ' pois ' by maximum likelihood

Parameters:

estimate Std. Error

lambda 4 0.6324555

#create 10 values from a real poisson distribution

dist = dpois(1:10, lambda = 4)

#multiply them by `sum(df$Freq)` in order to scale them to the barplot

dist = dist * sum(df$Freq)

#add the line plot to the original barplot

lines(dist, lwd = 2)

result

However, the curve is not smooth..

Answer Source

```
#fit poisson distr to tbl$Freq data
poisson = fitdist(df$Freq, 'pois', method = 'mle')
print(poisson)
#plot
plot(df$Var1, df$Freq, type = 'h', ylim = c(0,10), ylab = 'No. of years with x events',
xlab = 'No. of events in a year', main = 'All 13-day events with Poisson')
dist = dpois(1:10, lambda = 4)
dist = dist * sum(df$Freq)
dist = as.data.frame(dist)
dist$Var1 = df$Var1
lines(dist$Var1, dist$dist, lwd = 2)
```