Question: Let y i be a bin(n i =, i ) variate for group i, i = 1,..., N, with {y i } independent. Consider
Let yi be a bin(ni=, πi) variate for group i, i = 1,..., N, with {yi} independent. Consider the model that π1 = ... = πN. Denote that common value by π.
a. Show that the ML estimator of π is p = (∑i yi)/(∑i ni).
b. The minimum chi-squared estimator π̂ is the value of π minimizing
![[(:/m,) 1] N [(y:/n;) ] + TT i=1 i=1](https://dsd5zvtm8ll6.cloudfront.net/si.experts.images/questions/2022/11/636a768a05ea3_545636a7689e9ed1.jpg)
The second term results from comparing (1 − yi/ni) to (1 − π), the proportions in the second category. If n1 = ... = nN = 1, show that π̂ minimizes Np(1 − π)/π + N(1 − p)π/(1 − π). Hence show
π̂ = p1/2 / [p1/2 + (1 − p)1/2].
Note the bias toward 1/2 in this estimator.
c. Argue that as N ⇾ ∞ with all ni = 1, the ML estimator is consistent but the minimum chi-squared estimator is not (Mantel 1985).
[(:/m,) 1] N [(y:/n;) ] + TT i=1 i=1
Step by Step Solution
3.51 Rating (171 Votes )
There are 3 Steps involved in it
a To find the maximum likelihood estimator MLE of we need to maximize the likelihood function The likelihood function is given by L i1 to N binomialyi ni Taking the logarithm of the likelihood functio... View full answer
Get step-by-step solutions from verified subject matter experts
