On a point of information, the beta distribution is indeed
defined for x >= 0 and, respectively, for x <= 1 so long as
the parameters a="shape1" and b="shape2" are respectively
not less than 1:
dbeta(x,a,b) = (x^(a-1))*((1-x)^(b-1))/Beta(a,b)
When a=1 and b=1 we have the uniform distribution on
This is not very confusing. It is the exact same error in the sense that this
time the values of x1 are not only outside the interval (0-1) but within
[0-1] as in your first example, but this time they are also outside [0-1].
The reason is that you did not divide x1 by sum(x1) this time. In other
w
This is a theoretical issue. It is impossible for beta-distributed values to
take the value of 0 or 1. Hence, an attempt to fit a beta distribution to a
vector containing these values fails.
HTH,
Daniel
baxy77 wrote:
>
> Hi,
>
> Well, i need some help, practical and theoretical. I am wonderi
Hi,
Well, i need some help, practical and theoretical. I am wondering why the
fitdistplus (mle function) is returning an error for this code:
[code]
x1 <- c(100,200,140,98,97,56,42,10,2,2,1,4,3,2,12,3,1,1,1,1,0,0);
plotdist(x1);
descdist(x1, boot =1000);
y<- sum(x1);
d= as.vector(length(x1));
fo
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