Calculate p-value from Weibull distribution?
In the foloww up of my previous questionC: How to calculate probability of a value under Weibull distribution?. I have fitted a set of data into Weibull distribution and extract related parameters. Also, I have another set of data that I would like to calculate the p-value for each given value under the distribution.
I calculated the value of cumulative Weibull distribution for each point like below:
pweibull (x,scale,shape)
I would like to know can I use the value of pweibull directly as p-value or I should calculate like p-value= 1 - pweibull.
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by default it reports
P[X ≤ x]; if you wantP[X > x]you can addlower.tail = Fas parameterMany thanks for your reply. but for finding p-value shall I consider the value of the function itself or do 1- pweibull()?
You're getting the probability that X<=x or the probability that X>x for X following a Weibull distribution with the given parameters. The p-value is the probability of getting a value at least as big as what's observed if the null hypothesis is true. So whether you want to treat P[X>x] as p-value depends on whether you're testing the null hypothesis that X follows a Weibull distribution with the given parameters.
Thanks for your reply.
My data set is a kind of HiC data that shows the interaction between genomic regions. I would like to find the probability of observation which has stronger interaction under the Weibull distribution.
So the hypothesis is like: if x refers to background and X refers to observations.
H0: X<x< p="">
H1:X>x
In this case whether the p-value = 1-pweibull (X,weiull(parameters),lower.tail = F), or I am wrong?
Why did you re-open a new question? - here is your other one: How to calculate probability of a value under Weibull distribution?
Sorry, I think it is a different question than the previous one, but I put the link to the previous question.