Can you explain me about what is Maximum Likelihood Estimator
(MLE) for bernouli, normal, uniform, and...
Can you explain me about what is Maximum Likelihood Estimator
(MLE) for bernouli, normal, uniform, and poisson? How to use
it(example), and what is its relation with likelihood function?
Given a random sample from a uniform distribution, find the
maximum likelihood estimator for θ when
a) 0 ≤ x ≤ θ;
b) when 0 < x < θ;
c) when θ ≤ x ≤ θ + 1.
Determine the Maximum Likelihood Estimator for;
1. λ for the Poisson distribution.
2. θ for the Exponential distribution.
Caveat: These are examples of distributions for which the MLE
can be found analytically in terms of the data x1, . . . , xn and
so no advanced computational methods are required and also in each
assume a random sample of size n, x1, x2, . . . , xn
Econometrics Question:
Discuss the intuition behind the maximum likelihood estimator.
Discuss what, if any, desirable properties the maximum likelihood
estimator posseses.
suppose y has a normal distribution with mean=0 and var=theta.
a) what is the maximum likelihood estimator (mle) for
theta
b) show that the mle is unbiased for theta OR show it is
biased and construct an unbiased estimator based on it
catch me if you can (2002) write a report about catch me if you
can (2002) must be 900 words that fully describes
the movie including describing the main characters, the fraud
situation in the movie, and how the situation plays out. The second
part of the paper should discuss the actual persons and/or
companies on which the movie focuses: Identify these actual persons
/ company; identify the type(s) of fraud(s) are alleged in the
film; discuss your personal feelings...