MLE derivation for RV that follows Binomial distribution
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Looking at Cambridge stats notes (page 10). They have that $X sim B(n,p)$ and they show that the log likelihood of the data is maximized when $frac{x}{hat{p}}-frac{n-x}{1-hat{p}} = 0$. But when I derive this, I have a plus in there:
$$text{log likelihood}(p) = log f(x|p) = text{constant} + x log{p} + (n-x) log{1-p}$$
When you take a derivative of that with respect to $p$, you get:
$$frac{x}{p} + frac{n-x}{1-p}$$
What's wrong here?
statistics
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add a comment |
$begingroup$
Looking at Cambridge stats notes (page 10). They have that $X sim B(n,p)$ and they show that the log likelihood of the data is maximized when $frac{x}{hat{p}}-frac{n-x}{1-hat{p}} = 0$. But when I derive this, I have a plus in there:
$$text{log likelihood}(p) = log f(x|p) = text{constant} + x log{p} + (n-x) log{1-p}$$
When you take a derivative of that with respect to $p$, you get:
$$frac{x}{p} + frac{n-x}{1-p}$$
What's wrong here?
statistics
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ok I see... (1-p) in the third term..
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– i squared - Keep it Real
Dec 14 '18 at 11:24
add a comment |
$begingroup$
Looking at Cambridge stats notes (page 10). They have that $X sim B(n,p)$ and they show that the log likelihood of the data is maximized when $frac{x}{hat{p}}-frac{n-x}{1-hat{p}} = 0$. But when I derive this, I have a plus in there:
$$text{log likelihood}(p) = log f(x|p) = text{constant} + x log{p} + (n-x) log{1-p}$$
When you take a derivative of that with respect to $p$, you get:
$$frac{x}{p} + frac{n-x}{1-p}$$
What's wrong here?
statistics
$endgroup$
Looking at Cambridge stats notes (page 10). They have that $X sim B(n,p)$ and they show that the log likelihood of the data is maximized when $frac{x}{hat{p}}-frac{n-x}{1-hat{p}} = 0$. But when I derive this, I have a plus in there:
$$text{log likelihood}(p) = log f(x|p) = text{constant} + x log{p} + (n-x) log{1-p}$$
When you take a derivative of that with respect to $p$, you get:
$$frac{x}{p} + frac{n-x}{1-p}$$
What's wrong here?
statistics
statistics
asked Dec 14 '18 at 11:22
i squared - Keep it Reali squared - Keep it Real
1,5851925
1,5851925
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ok I see... (1-p) in the third term..
$endgroup$
– i squared - Keep it Real
Dec 14 '18 at 11:24
add a comment |
$begingroup$
ok I see... (1-p) in the third term..
$endgroup$
– i squared - Keep it Real
Dec 14 '18 at 11:24
$begingroup$
ok I see... (1-p) in the third term..
$endgroup$
– i squared - Keep it Real
Dec 14 '18 at 11:24
$begingroup$
ok I see... (1-p) in the third term..
$endgroup$
– i squared - Keep it Real
Dec 14 '18 at 11:24
add a comment |
1 Answer
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As we differentiate, we use chain rule
$$frac{d}{dp}(xlog p + (n-x) log (1-p))= frac{x}{p}+frac{n-x}{1-p}frac{d}{dp}(1-p)=frac{x}{p}-frac{n-x}{1-p}$$
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1 Answer
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1 Answer
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$begingroup$
As we differentiate, we use chain rule
$$frac{d}{dp}(xlog p + (n-x) log (1-p))= frac{x}{p}+frac{n-x}{1-p}frac{d}{dp}(1-p)=frac{x}{p}-frac{n-x}{1-p}$$
$endgroup$
add a comment |
$begingroup$
As we differentiate, we use chain rule
$$frac{d}{dp}(xlog p + (n-x) log (1-p))= frac{x}{p}+frac{n-x}{1-p}frac{d}{dp}(1-p)=frac{x}{p}-frac{n-x}{1-p}$$
$endgroup$
add a comment |
$begingroup$
As we differentiate, we use chain rule
$$frac{d}{dp}(xlog p + (n-x) log (1-p))= frac{x}{p}+frac{n-x}{1-p}frac{d}{dp}(1-p)=frac{x}{p}-frac{n-x}{1-p}$$
$endgroup$
As we differentiate, we use chain rule
$$frac{d}{dp}(xlog p + (n-x) log (1-p))= frac{x}{p}+frac{n-x}{1-p}frac{d}{dp}(1-p)=frac{x}{p}-frac{n-x}{1-p}$$
answered Dec 14 '18 at 11:57
Siong Thye GohSiong Thye Goh
100k1465117
100k1465117
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$begingroup$
ok I see... (1-p) in the third term..
$endgroup$
– i squared - Keep it Real
Dec 14 '18 at 11:24