PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE
In the statistical modeling framework, the form of the income distribution can be approaching based on certain statistical distributions. The use of the finite mixture model is relatively flexible in the modeling of the income distribution that has a multimodal pattern. The multimodal pattern can be...
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doaj-99f80f6f3a2242fb98295f726e6dc4252020-11-25T03:39:27ZengUniversitas DiponegoroMedia Statistika1979-36932477-06472020-06-01131132410.14710/medstat.13.1.13-2416934PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTUREIrwan Susanto0Sri Sulistijowati Handajani1Program Studi Statistika, FMIPA, Universitas Sebelas MaretProgram Studi Statistika, FMIPA, Universitas Sebelas MaretIn the statistical modeling framework, the form of the income distribution can be approaching based on certain statistical distributions. The use of the finite mixture model is relatively flexible in the modeling of the income distribution that has a multimodal pattern. The multimodal pattern can be indicated as the existence of different cluster on the data. The different clusters which can reflect the economic homogeneity of income are represented by the mixture components of the finite mixture model. In this paper, the finite mixture model is implemented for modeling the distribution of household income per capita in Indonesia based on The Fifth Wave of the Indonesia Family Life Survey (IFLS5) 2014-2015. The mixture components of the finite mixture model have been build based on the heavy-tailed statistical distributions, i.e., gamma, lognormal, and Weibull distributions. The estimation of the fitting finite mixture model was conducted using the maximum-likelihood estimation method through the expectation-maximization (EM) algorithm. The suitable finite mixture models were verified with the bootstrap likelihood ratio statistics test, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Based on the results, the distribution of household income per capita in Indonesia can be modeled by the four components-lognormal mixture model.https://ejournal.undip.ac.id/index.php/media_statistika/article/view/22904 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Irwan Susanto Sri Sulistijowati Handajani |
spellingShingle |
Irwan Susanto Sri Sulistijowati Handajani PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE Media Statistika |
author_facet |
Irwan Susanto Sri Sulistijowati Handajani |
author_sort |
Irwan Susanto |
title |
PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE |
title_short |
PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE |
title_full |
PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE |
title_fullStr |
PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE |
title_full_unstemmed |
PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE |
title_sort |
pengelompokan rumah tangga di indonesia berdasarkan pendapatan per kapita dengan model finite mixture |
publisher |
Universitas Diponegoro |
series |
Media Statistika |
issn |
1979-3693 2477-0647 |
publishDate |
2020-06-01 |
description |
In the statistical modeling framework, the form of the income distribution can be approaching based on certain statistical distributions. The use of the finite mixture model is relatively flexible in the modeling of the income distribution that has a multimodal pattern. The multimodal pattern can be indicated as the existence of different cluster on the data. The different clusters which can reflect the economic homogeneity of income are represented by the mixture components of the finite mixture model. In this paper, the finite mixture model is implemented for modeling the distribution of household income per capita in Indonesia based on The Fifth Wave of the Indonesia Family Life Survey (IFLS5) 2014-2015. The mixture components of the finite mixture model have been build based on the heavy-tailed statistical distributions, i.e., gamma, lognormal, and Weibull distributions. The estimation of the fitting finite mixture model was conducted using the maximum-likelihood estimation method through the expectation-maximization (EM) algorithm. The suitable finite mixture models were verified with the bootstrap likelihood ratio statistics test, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Based on the results, the distribution of household income per capita in Indonesia can be modeled by the four components-lognormal mixture model. |
url |
https://ejournal.undip.ac.id/index.php/media_statistika/article/view/22904 |
work_keys_str_mv |
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