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This was uploaded 7 years ago, yet it's still saving carees. Thank you so much.
At 1:23 should the it be x^a-1? I’m seeing different resources using either x or lambda
thank you very much , this is a very clear video. could you please provide me a link the explain an inverse Gaussian distribution with power normal prior. thanks.
thnks from Brazil
Thank you sooo much!! Very clear!
Well understood. Many thanks!!!
i love you for this
hi, i have a question: is it possible to compute the joint distribution of the poisson? π(lambda,X1,...,Xn)?
Dear Sir Please tell how we will deal with if summation (1 to N)(theta -x) as you told summation (1 to N)(X)=N.Xbar
I think you'd just simplify as such:sum( theta - x_i ) = sum(theta) - sum(x_i) = n*theta - n*xbar = n(theta - xbar)
@@choendenkyirong8313 Thankyou so much Sir
That was excellent
wow thanks so much for the info
thakns for sketching out
This was uploaded 7 years ago, yet it's still saving carees. Thank you so much.
At 1:23 should the it be x^a-1? I’m seeing different resources using either x or lambda
thank you very much , this is a very clear video.
could you please provide me a link the explain an inverse Gaussian distribution with power normal prior.
thanks.
thnks from Brazil
Thank you sooo much!! Very clear!
Well understood. Many thanks!!!
i love you for this
hi, i have a question: is it possible to compute the joint distribution of the poisson? π(lambda,X1,...,Xn)?
Dear Sir Please tell how we will deal with if summation (1 to N)(theta -x) as you told summation (1 to N)(X)=N.Xbar
I think you'd just simplify as such:
sum( theta - x_i ) = sum(theta) - sum(x_i) = n*theta - n*xbar = n(theta - xbar)
@@choendenkyirong8313 Thankyou so much Sir
That was excellent
wow thanks so much for the info
thakns for sketching out