Suppose X1,X2,...,Xn is a RS from Bernoulli distribution. Define the estimator theta hat=1/n+√n( summation Xi+√n/n) Show that theta hat is a consistent estimator of theta
estimator of Bernoulli distribution:
"\\theta=p=\\frac{\\sum x_i}{n}"
"\\hat{\\theta }" is a consistent estimator if
"\\displaystyle \\lim_{n\\to \\infin} Pr(|\\hat{\\theta}-\\theta|> \\varepsilon)=0"
for all "\\varepsilon >0"
then:
"\\hat{\\theta}-\\theta=\\frac{1}{n+\\sqrt n}( \\sum x_i+\\sqrt n)\/n-\\frac{\\sum x_i}{n}"
"\\displaystyle \\lim_{n\\to \\infin}|\\hat{\\theta}-\\theta|=0"
"\\displaystyle \\lim_{n\\to \\infin} Pr(0> \\varepsilon)=0"
so, "\\hat{\\theta }" is a consistent estimator of "\\theta"
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