Let (Xi) sim N(i theta, 1) for i=1,....,n be an independent, but not identically distributed sample. Check that T = sum_i X_i it is a sufficient statistic for theta.

Anton Huynh

Anton Huynh

Answered question

2022-11-03

Let { X i } N ( i θ , 1 ) for i = 1 , . . . . , n be an independent, but not identically distributed sample. Check that T = i X i it is a sufficient statistic for θ .

Answer & Explanation

Ryan Davies

Ryan Davies

Beginner2022-11-04Added 18 answers

We have that the probability density function of X i is
f X i ( x i ) = 1 2 π exp [ 1 2 ( x i i θ ) 2 ] .
By independence, the joint density is given by
f X 1 , , X n ( x 1 , , x n ) = i = 1 n f X i ( x i ) = 1 ( 2 π ) n / 2 exp [ 1 2 i = 1 n ( x i i θ ) 2 ] .
Now we expand the sum:
i = 1 n ( x i i θ ) 2 = i = 1 n x i 2 2 θ i = 1 n i x i + θ i = 1 n i 2 .
Recalling the sum
i = 1 n i 2 = n ( n + 1 ) ( 2 n + 1 ) 6
we obtain
i = 1 n ( x i i θ ) 2 = i = 1 n x i 2 + θ [ n ( n + 1 ) ( 2 n + 1 ) 6 2 i = 1 n i x i ] .
The joint density may thus be written as
1 ( 2 π ) n / 2 exp [ 1 2 i = 1 n x i 2 ] h ( x ) exp { θ [ n ( n + 1 ) ( 2 n + 1 ) 6 2 i = 1 n i x i ] } φ ( i = 1 n i x i , θ ) .
By the factorization criterion, i = 1 n i X i is sufficient for θ.
i = 1 n X i is sufficient for θ.

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