(a) Describe how the two commonly used parameter estimation methods (method of moment and percentile matching) are applied in fitting distributions to data in actuarial calculations. (b) The following table is a frequency distribution for claim size (£'000). Claim size: 0-1 1-2 2-4 4-8 8-16 16-32 No of claims: 236 125 76 48 12 3 (i) (ii) Estimate parameters for fitting a Log Normal distribution to the above data by using the method of moment. Carry out a goodness of fit test and comment on results. If the average number of claims per year is 48 then calculate the total claim size per year that will only be exceeded once in 1000 times. Use a skewness correction and present your results clearly.

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(a)
(b)
Describe how the two commonly used parameter estimation methods (method
of moment and percentile matching) are applied in fitting distributions to data
in actuarial calculations.
The following table is a frequency distribution for claim size (£'000).
Claim size: 0-1
1-2
2-4
4-8
8-16
16-32
No of claims: 236
125
76
48
12
3
(i)
(ii)
Estimate parameters for fitting a Log Normal distribution to the above
data by using the method of moment. Carry out a goodness of fit test and
comment on results.
If the average number of claims per year is 48 then calculate the total
claim size per year that will only be exceeded once in 1000 times. Use
a skewness correction and present your results clearly.
Transcribed Image Text:(a) (b) Describe how the two commonly used parameter estimation methods (method of moment and percentile matching) are applied in fitting distributions to data in actuarial calculations. The following table is a frequency distribution for claim size (£'000). Claim size: 0-1 1-2 2-4 4-8 8-16 16-32 No of claims: 236 125 76 48 12 3 (i) (ii) Estimate parameters for fitting a Log Normal distribution to the above data by using the method of moment. Carry out a goodness of fit test and comment on results. If the average number of claims per year is 48 then calculate the total claim size per year that will only be exceeded once in 1000 times. Use a skewness correction and present your results clearly.
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