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
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)
}
Hi please can you also do these iterations using the method of scoring to estimate the parameter if possible
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.