Let X1, X2, ..., Xn be a random sample of size n from the
distribution with probability density function
To answer this question, enter you answer as a formula. In
addition to the usual guidelines, two more instructions for this
problem only : write
as single variable p and
as m. and these can be used as inputs of functions as usual
variables e.g log(p), m^2, exp(m) etc. Remember p represents the
product of
s only, but will not work for the product of any function of
.
1. Find the maximum likelihood estimator of
2. Suppose
. Find the method of moments estimator of
. Use the sqrt(x) formula for square root.
Let X1, X2, ..., Xn be a random sample of size n from the distribution with...
Let X1, X2, ..., Xn be a random
sample from X which has pdf
depending on a parameter
and
(i)
(ii)
where
< x <
. In both these two cases
a) write down the log-likelihood function and find a
1-dimensional sufficient statistic for
b) find the score function and the maximum likelihood estimator
of
c) find the observed information and evaluate the Fisher
information at
= 1.
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Let X1, X2,.. .Xn be a random sample of size n from a distribution with probability density function obtain the maximum likelihood estimator of θ, θ. Use this maximum likelihood estimator to obtain an estimate of P[X > 4 when 0.50, 2 1.50, x 4.00, 4 3.00.
PROBLEM 3 Let X1, X2, ..., Xn be a random sample from the following distribution - 5) +1 if 0 <r <1 fx(2) = 10 0. 0.w.. where @ € (-2, 2) is an unknown parameter. We define the estimate ēn as: ô, = 12X – 6 to estimate . (a) Is ên an unbiased estimator of e? (b) Is Ôn a consistent estimator of e?
Let X1, . . . , Xn be a random sample from
a triangular probability distribution whose density function and
moments are:
fX(x) =
* I{0
x
b}
a. Find the mean µ of this probability
distribution.
b. Find the Method Of Moments estimator µ(hat) of µ.
c. Is µ(hat) unbiased?
d. Find the Median of this probability distribution.
I will thumbs up any portion or details of how to do this
problem, thanks!
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Let X1, X2,.......Xn be a
random sample of size n from a continuous distribution symmetric
about .
For testing H0: =
10 vs H1: <
10, consider the statistic T- =
Ri+ (1-i),
where i
=1 if Xi>10 , 0 otherwise; and
Ri+ is the rank of (Xi - 10) among
|X1 -10|, |X2-10|......|Xn
-10|.
1. Find the null mean and variance of T- .
2. Find the exact null distribution of T- for
n=5.
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5. Let X1, X2,. , Xn be a random sample from a distribution with pdf of f(x) (0+1)x,0< x<1 a. What is the moment estimator for 0 using the method of moments technique? b. What is the MLE for 0?
Let X1, X2, ..., Xn be a random sample from a Gamma( a , ) distribution. That is, f(x;a,0) = loga xa-le-210, 0 < x <co, a>0,0 > 0. Suppose a is known. a. Obtain a method of moments estimator of 0, 0. b. Obtain the maximum likelihood estimator of 0, 0. c. Is O an unbiased estimator for 0 ? Justify your answer. "Hint": E(X) = p. d. Find Var(ë). "Hint": Var(X) = o/n. e. Find MSE(Ô).
5. Let X1, X2, ..., Xn be a random sample from a distribution with pdf of f(x) = (@+1)xº,0<x<1. a. What is the moment estimator for 0 using the method of moments technique? b. What is the MLE for @ ?
6. Let X1, X2,.. , Xn denote a random sample of size n> 1 from a distribution with pdf f(x; 6) = 6e-8, 0<x< 20, zero elsewhere, and 0 > 0. Le Y = x. (a) Show that Y is a sufficient and complete statistics for . (b) Prove that (n-1)/Y is an unbiased estimator of 0.
A Pareto distribution is often used in economics to explain a
distribution of wealth. Let a random variable X have a Pareto
distribution with parameter θ so that its probability distribution
function is
for
and 0 otherwise. The parameters and
are
known and fixed; is a constant to
be determined.
a) Assuming that
find the expected value and variance of ?
b) Show that for 3 ≥ θ > 2 the Pareto distribution has a
finite mean but infinite variance,...