0:00 Introduction and review 1:28 Generating sample data 4:52 Define the partial derivative wrt α as a function. 6:42 Finding the value of α hat 8:41 Finding the value of λ hat
don't have the same result with this command for likelihood for negative exponential distribution: L1=dgamma(theta1,shape=n,rate=sum(x)) L.NEXP=function(x,theta){ n=length(x) s=sum(x) L=(theta^n)*exp(-theta*s) return(L) }
Awesome video, very clear - hopefully more stats videos
0:00 Introduction and review
1:28 Generating sample data
4:52 Define the partial derivative wrt α as a function.
6:42 Finding the value of α hat
8:41 Finding the value of λ hat
Hi please can you also do these iterations using the method of scoring to estimate the parameter if possible
don't have the same result with this command for likelihood for negative exponential distribution: L1=dgamma(theta1,shape=n,rate=sum(x))
L.NEXP=function(x,theta){
n=length(x)
s=sum(x)
L=(theta^n)*exp(-theta*s)
return(L)
}
How to calculate 2 and 0.2? kindly send me the programming i have the data and i want to calculate thier parameters,
The link to the code is in the description.