Module Catalogues, Xi'an Jiaotong-Liverpool University   
Module Code: MTH313
Module Title: Loss Distribution
Module Level: Level 3
Module Credits: 5.00
Academic Year: 2020/21
Semester: SEM1
Originating Department: Mathematical Sciences
Pre-requisites: MTH206 MTH223
This module provides solid probabilistic and statistical tools to estimate parameters for a variety of actuarial models. Students are also required to understand the hypothesis tests and goodness of fit. Students gain the ability to design models according to different type of data.
Learning outcomes 
A. Apply mathematical, statistical and probabilistic skills to solve actuarial models.

B. Perform the estimation for complete and modified data

C. Estimate parameters: point estimation, moment estimation, maximum likelihood estimation

D. Select models based on hypothesis tests

E. Apply estimation and model selection to more complex models

F. Analyze different actuarial models
Method of teaching and learning 
This module is delivered through formal lectures and tutorial classes
1. Point estimation, interval estimation, the empirical distribution for complete, individual and grouped data, estimation for modified data.

2. Maximum likelihood estimation (MLE) for loss frequency distributions ; Poisson, negative binomial , binomial and the (a,b,0), and (a,b,1).

3. MLE based on complete individual and grouped data, MLE for truncated or censored data.

4. Variance and interval estimation

5. Meaning of loss function. Fundamental concepts of Bayesian statistics; Bayesian estimation calculation,

6. Model testing: chi-square goodness of fit test, the likelihood ration test, Kolmogorov-Smirnov test and Anderson-Darling test.

7. Extreme value models, copula models, applications to different actuarial data.

Delivery Hours  
Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total
Hours/Semester 39    13      98  150 


Sequence Method % of Final Mark
1 Assignments 15.00
2 Midterm Exam 15.00
3 Final Exam 70.00

Module Catalogue generated from SITS CUT-OFF: 6/4/2020 6:59:26 AM