Answer to Question #201200 in Statistics and Probability for Biniyam yirgalem

Question #201200

A random sampleY1 , Y 2 , ⋯,Yn is drawn from a distribution whose probability density function is given by: f (Y ) = βe − βY , Y  0 & β > 0 a). Obtain the maximum likelihood estimator (MLE) of β. (3 points) 1Econometrics- Assignment I b). Given that ∑ n Y i = 25 , ∑n Yi 2 = 50 , n = 50 calculate the maximum likelihood i =1 i =1 estimate of β. (3 point) c). Using the same data as in part (b), test the null hypothesis that β =1against the alternative hypothesis that β ≠1at 5% level of significance


1
Expert's answer
2021-07-05T06:43:18-0400

(a)From the given information, the probability density function is,

"f(y)=\u03b2e^{\u2212\u03b2y}, y>0, \u03b2>0 ."

Consider, the likelihood function,

"L(y)=\u220f^{n}_{i=1}f(y) \\\\ =f(y1)*f(y2)*.....*f(y_n) \\\\ =\u03b2e^{\u2212\u03b2y1}*\u03b2e^{\u2212\u03b2y2}*............*\u03b2e^{\u2212\u03b2y_n } \\\\\\ =\u03b2^{n}e^{\u2212\u03b2}\u2211yi"

Consider, ln on both sides

"lnL(y)=ln[\u03b2^{n}e^{\u2212\u03b2}\u2211y_i] \\\\ =nln\u03b2\u2212\u03b2\u2211yi"

Therefore,

"\\frac{dlnL(y)}{d\u03b2}=0\\\\\\frac{n}{\u03b2}\u2212\u2211Yi=0 \\\\ \\frac{ n}{\u03b2}=\u2211Yi \\\\ \u03b2\u02c6=\\frac{1}{y}"


"b)\\\\\n\n \u2211 Y i = 25 , \u2211 Yi^2= 50 , n = 50 \\\\\n\nTherefore,\\\\\n\n \u03b2\u02c6=\\frac{1}{y}\\\\=\\frac{1}{\\frac{25}{50}} \\\\ =2"


(c)null hypothesis that β =1against the alternative hypothesis that β ≠1at 5% level of significance.

Null Hypothesis:

H0: β =1

Alternative Hypothesis:

H1: β ≠1

Consider, the likelihood ratio,

"\\frac{L(y )H_0}{L(y)H_1}=\\frac{1^{n}e\u22121\u2211y_i}{\u03b2^{n}e^{\u2212\u03b2}\u2211y_i }\\\\ =(\\frac{1}{\u03b2})^{n}e^{(\u03b2\u22121)\u2211y}\\\\ln\\frac{L(y )H_0}{L(y)H_1}=nln(\\frac{1}{\u03b2})+(\u03b2\u22121)\u2211y"

Critical region is,

"ln\\frac{L(y )_{H_0}}{L(y)_{H_1}}\u2264c\\\\nln(\\frac{1}{\u03b2})+(\u03b2\u22121)\u2211y\u2264c\\\\(\u03b2\u22121)\u2211y\u2264c\u2212nln(\\frac{1}{\u03b2}) \\\\ \u2211y\u2264\\frac{c\u2212nln(\\frac{1}{\u03b2})}{(\u03b2\u22121) }\\\\ \u2211y\u2264c',\\frac{c\u2212nln(\\frac{1}{\u03b2})}{(\u03b2\u22121)}=c'"

Thus, reject the null hypothesis if, "\u2211y\u2264c'"  



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