Truncated Spline Estimation of Percentage Poverty Modeling in Papua Province

Authors

  • Ni Putu Ayu Mirah Mariati Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia 2Universitas Mahasaraswati, Denpasar Bali, 80233, Indonesia
  • Nyoman Budiantara Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia
  • Vita Ratnasari Universitas Mahasaraswati, Denpasar Bali, 80233, Indonesia

DOI:

https://doi.org/10.29244/icsa.2019.pp69-82

Keywords:

nonparametric regression, poverty, truncated spline

Abstract

In estimating the regression curve there are three approaches, namely parametric regression, nonparametric regression and semiparametric regression. Nonparametric regression approach has high flexibility. Nonparametric regression approach that is quite popular is Truncated Spline. Truncated Spline is a polynomial pieces which have segmented and continuous. One of the advantages of Spline is that it can handle data that changes at certain sub intervals, so this model tends to search for data estimates wherever the data pattern moves and there are points of knots. In reality, data patterns often change at certain sub intervals, one of which is data on poverty in the Papua Province. Papua Province is ranked first in the percentage of poor people in Indonesia. The best of model Truncated Spline in nonparametric regression for the poverty model in Papua Province is using a combination of knot.

 

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Published

2021-02-26