FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL
<p align="justify">Claim-frequency, besides claim-severity, is an important part of (insurance) claim. Forecasting claim-frequency can be determined by employing integer-valued autoregressive or INAR model. There are two aspects of such model: number of claim processed during certain...
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id-itb.:265592018-09-18T08:58:09ZFORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL NOVIANTI (NIM : 20113018), DEWI Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/26559 <p align="justify">Claim-frequency, besides claim-severity, is an important part of (insurance) claim. Forecasting claim-frequency can be determined by employing integer-valued autoregressive or INAR model. There are two aspects of such model: number of claim processed during certain period of time (survival) and number of claim arrived up to certain time (arrival); the latter is called innovation. In this thesis, we deal with innovation following compound-Poisson distribution. This represents aggregate claims. The resulting model is named as CPINAR; specifically we have used CPINAR-Poisson and CPINAR-logarithmic. Claimfrequency predicted by CPINAR model involves calculating conditional mean and unstraightforward probability. The method of estimation used are least squared and maximum. likelihood.<p align="justify"> text |
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<p align="justify">Claim-frequency, besides claim-severity, is an important part of (insurance) claim. Forecasting claim-frequency can be determined by employing integer-valued autoregressive or INAR model. There are two aspects of such model: number of claim processed during certain period of time (survival) and number of claim arrived up to certain time (arrival); the latter is called innovation. In this thesis, we deal with innovation following compound-Poisson distribution. This represents aggregate claims. The resulting model is named as CPINAR; specifically we have used CPINAR-Poisson and CPINAR-logarithmic. Claimfrequency predicted by CPINAR model involves calculating conditional mean and unstraightforward probability. The method of estimation used are least squared and maximum. likelihood.<p align="justify"> |
| format |
Theses |
| author |
NOVIANTI (NIM : 20113018), DEWI |
| spellingShingle |
NOVIANTI (NIM : 20113018), DEWI FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL |
| author_facet |
NOVIANTI (NIM : 20113018), DEWI |
| author_sort |
NOVIANTI (NIM : 20113018), DEWI |
| title |
FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL |
| title_short |
FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL |
| title_full |
FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL |
| title_fullStr |
FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL |
| title_full_unstemmed |
FORECASTING CLAIM FREQUENCY BY USING FIRST-ORDER CPINAR MODEL |
| title_sort |
forecasting claim frequency by using first-order cpinar model |
| url |
https://digilib.itb.ac.id/gdl/view/26559 |
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1822021048472698880 |