Predicting number of purchasing life insurance using Markov chain method

Mohd Rahimie Bin Md Noor, Zaidi Isa

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This study describes the Markov chain approach applied in forecasting the life insurance buying patterns. This model using a sample purchase life insurance from General Assurance Berhad covering the years 2003-2006. Markov chain model built is kind of the first stage with a homogeneous time. This model uses the idea (stop-motion) to clarify the circumstances of the number and time of purchase. At the end of the study show how the Markov chain to be a good method in predicting. Therefore, this method should be extended in various fields.

Original languageEnglish
Pages (from-to)4087-4095
Number of pages9
JournalApplied Mathematical Sciences
Issue number81-84
DOIs
Publication statusPublished - 2014

Fingerprint

Purchasing
Insurance
Markov processes
Markov chain
Markov Chain Model
Forecasting
Covering
Motion
Model
Life

Keywords

  • Homogeneous time
  • Markov-chain
  • Stochastic process

ASJC Scopus subject areas

  • Applied Mathematics

Cite this

Predicting number of purchasing life insurance using Markov chain method. / Noor, Mohd Rahimie Bin Md; Isa, Zaidi.

In: Applied Mathematical Sciences, No. 81-84, 2014, p. 4087-4095.

Research output: Contribution to journalArticle

@article{085c7f9c2eb443d79fc9b6c13b0d2ec7,
title = "Predicting number of purchasing life insurance using Markov chain method",
abstract = "This study describes the Markov chain approach applied in forecasting the life insurance buying patterns. This model using a sample purchase life insurance from General Assurance Berhad covering the years 2003-2006. Markov chain model built is kind of the first stage with a homogeneous time. This model uses the idea (stop-motion) to clarify the circumstances of the number and time of purchase. At the end of the study show how the Markov chain to be a good method in predicting. Therefore, this method should be extended in various fields.",
keywords = "Homogeneous time, Markov-chain, Stochastic process",
author = "Noor, {Mohd Rahimie Bin Md} and Zaidi Isa",
year = "2014",
doi = "10.12988/ams.2014.45383",
language = "English",
pages = "4087--4095",
journal = "Applied Mathematical Sciences",
issn = "1312-885X",
publisher = "Hikari Ltd.",
number = "81-84",

}

TY - JOUR

T1 - Predicting number of purchasing life insurance using Markov chain method

AU - Noor, Mohd Rahimie Bin Md

AU - Isa, Zaidi

PY - 2014

Y1 - 2014

N2 - This study describes the Markov chain approach applied in forecasting the life insurance buying patterns. This model using a sample purchase life insurance from General Assurance Berhad covering the years 2003-2006. Markov chain model built is kind of the first stage with a homogeneous time. This model uses the idea (stop-motion) to clarify the circumstances of the number and time of purchase. At the end of the study show how the Markov chain to be a good method in predicting. Therefore, this method should be extended in various fields.

AB - This study describes the Markov chain approach applied in forecasting the life insurance buying patterns. This model using a sample purchase life insurance from General Assurance Berhad covering the years 2003-2006. Markov chain model built is kind of the first stage with a homogeneous time. This model uses the idea (stop-motion) to clarify the circumstances of the number and time of purchase. At the end of the study show how the Markov chain to be a good method in predicting. Therefore, this method should be extended in various fields.

KW - Homogeneous time

KW - Markov-chain

KW - Stochastic process

UR - http://www.scopus.com/inward/record.url?scp=84903825115&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84903825115&partnerID=8YFLogxK

U2 - 10.12988/ams.2014.45383

DO - 10.12988/ams.2014.45383

M3 - Article

AN - SCOPUS:84903825115

SP - 4087

EP - 4095

JO - Applied Mathematical Sciences

JF - Applied Mathematical Sciences

SN - 1312-885X

IS - 81-84

ER -