Negative binomial probability function:


is the mean
is the dispersion
parameter
Let there be two groups with numbers
and means of

1) Write down the log-likelihood for the full model
2) Calculate the likelihood equations and find the general form
of the MLE for
and 
3) Write down the likelihood function in the reduced model (ie.
assuming
)
and derive the MLE for
in general
terms
4) Using the above answers only, give the MLE and standard error
for
where
5) Compute the expected information and the asymptotic variance-covariance matrix of the MLEs in the full model
6) Give the formula for an approximate Wald test of 
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Negative binomial probability function: is the mean is the dispersion parameter Let there be two groups...
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,...
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
be a simple random sample of a random variable X with density
function
, .
Given the statistic :
Calculate a statistic ( function of ) such that its espected
value is equal to
.
Thank you for your explanations
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(6) The sequence of random variable
are independent of each other and they follow the normal
distribution
.
However, the actual value of were not
observed, instead we only observed if each is either
greater than or
equal to 0, or less than 0.
And you can use the fact that there is the inverse function
that is continuous.
Answer the following questions.
Find
the maximum likelihood estimator
of .
When
, show
, where
represents conversion of probability....
Let be the distribution
function defined by
Let be the
Lebesgue-Stieltjes measure asociated to .
Determine the measurements of the fpllowing sets:
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Write A function Markov that take ?, ? and ? as inputs and
return the upper bounds for ?(?≥?⋅??) given by the below Markov
inequalities as output.
For the binomial distribution
with mean and variance
,
we would like to upper bound the probability
for .
Example:
Markov(100.,0.2,1.5)
Output:
0.6666666666666666
Which of the following is the correct output for
Markov(200.,0.3,1.1)?
A. 0.909
B 0.558
C. 0.986
D. 0872
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PART C
Problem 3. Let Xi.X^...be i.d. sample from a Rayleigh distribution, with parameter > 0: x2 262x> 0 02 We separately computed the ECX2) and found that Ex 28 (a) Find the likelihood function simplifying it as much as possible. Likelihood- We were unable to transcribe this image
Let X be a banach space such that X= C([a,b]) where - ab+ with the sup
norm. Let x and f X. Show
that the non linear integral equation
u(x) = (sin
u(y) dy + f(x) ) has a solution u X. (the integral is
from a to b).
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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...
Prove, or give a counter example to disprove the following
statements.
a)
b)
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