LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034
B.Sc.
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DEGREE EXAMINATION –STATISTICS
FIFTH SEMESTER – APRIL 2007
ST 5500 – ESTIMATION THEORY
Date & Time: 27/04/2007 / 1:00 – 4:00 Dept. No. Max. : 100 Marks
Part A
Answer all the questions. 10 X 2 = 20
- State the problem of point estimation.
- Define asymptotically unbiased estimator.
- Define a consistent estimator and give an example.
- Explain minimum variance bound estimator.
- What is Fisher information?
- Write a note on bounded completeness.
- Examine if { N (0, σ2), σ2 > 0 } is complete.
- Let X1, X2 denote a random sample of size 2 from P(q),q > 0. Show that X1 + 2X2 is not sufficient for q.
- State Chapman – Robbins inequality.
- Explain linear estimation.
Part B
Answer any five questions. 5 X 8 = 40
- Let X1, X2, … ,Xn denote a random sample of size n from B(1,q), 0<q<1. Show that is an unbiased estimator of q2, where T = .
- If Tn is consistent for Y(q) and g is continuous, show that g(Tn ) is consistent for g{Y(q)}.
- State and establish Cramer – Rao inequality.
- Show that the family of binomial distributions { B (n, p), 0 < p < 1, n fixed } is complete.
- State and establish Rao – Blackwell theorem.
- Let X1, X2, … , Xn denote a random sample of size n from U (0, q), q > 0.
Obtain the UMVUE of q.
- Give an example for each of the following
- MLE, which is not unbiased.
- MLE, which is not sufficient.
- Describe the method of minimum chi-square and the method of modified minimum
chi-square.
Part C
Answer any two questions. 2 X 20 = 40
- a). Show that the sample variance is a biased estimator of the population variance.
Suggest an unbiased estimator of s2.
b). If Tn is asymptotically unbiased with variance approaching zero as n
approaches infinity then show that Tn is consistent. (10 + 10)
- a). Let X1, X2, … , Xn denote a random sample of size n from U (q-1, q +1).
Show that the mid – range U = is an unbiased estimator of q.
b). Obtain the estimator of p based on a random sample of size n from
B(1, p), 0 < p < 1by the method of
i). Minimum chi-square
ii). Modified minimum chi-square. (12 + 8)
- a). Give an example to show that bounded completeness does not imply completeness.
b). Stat and prove invariance property of MLE. (10 +10)
- a). State and establish Bhattacharyya inequality.
b). Write short notes on Bayes estimation. (12 + 8)
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