We are given the probability density function of a t-distribution t(µ, 1) (shown in attached image): The task is to Write down the log-likelihood function of 200 samples, derive the first and second derivative of the log likelihood function with respect to µ. I got log-likihood function for 200 sampes and the first derivative, but am having trouble figuring how to get the second derivative.

MATLAB: An Introduction with Applications
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We are given the probability density function of a t-distribution t(µ, 1) (shown in attached image): The task is to Write down the log-likelihood function of 200 samples, derive the first and second derivative of the log likelihood function with respect to µ. I got log-likihood function for 200 sampes and the first derivative, but am having trouble figuring how to get the second derivative.

f(y):
1
T()√√
(1 + (y-μ)²)-¹.
Transcribed Image Text:f(y): 1 T()√√ (1 + (y-μ)²)-¹.
Question
-200 Samples 1 deg. Freedom, unknown location Paremeter uit (1,1)
a POF → f(y) = 1
T (²) √ (1 + (x-1)²) = 1
log
ikinas f (Vi) (412) -√7) (1 + (Y-μ)²) = 1
(200
sommes)
1st-
· 2 (M/Yi) = log f (Vi) = C-log (1 + (Vi _u)²)
· 2 (MK²)
(y)
зм
Ind.
deristike 3
32" (MY)
u
2.00
= log (f(x)) = log (it+ ₁ f(x)) = = = = log (f (vi)) = 200 ^ C
→ ²log (1 + (√²-1) ²
200
cancels since we mulive vbx -2
200
2
=X²-2²2 1 + (K-M) ²
-each of the y different
dotopar
Transcribed Image Text:Question -200 Samples 1 deg. Freedom, unknown location Paremeter uit (1,1) a POF → f(y) = 1 T (²) √ (1 + (x-1)²) = 1 log ikinas f (Vi) (412) -√7) (1 + (Y-μ)²) = 1 (200 sommes) 1st- · 2 (M/Yi) = log f (Vi) = C-log (1 + (Vi _u)²) · 2 (MK²) (y) зм Ind. deristike 3 32" (MY) u 2.00 = log (f(x)) = log (it+ ₁ f(x)) = = = = log (f (vi)) = 200 ^ C → ²log (1 + (√²-1) ² 200 cancels since we mulive vbx -2 200 2 =X²-2²2 1 + (K-M) ² -each of the y different dotopar
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