Umami, Riza and Nisa, Khoirin (2020) Pendugaan Model Time Varying Parameter Menggunakan Algoritma Kalman Filter. In: Seminar Nasional Sains, Matematika, Informatika, dan Aplikasinya (SMIAP), 24-25 Oktober 2019, Universitas Lampung.

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Abstract

The Time Varying Parameter (TVP) model is a univariate time series model, where the parameters vary with time. The TVP model is specified in the state space model and is estimated by the Kalman Filter algorithm. Estimation of the model in the Kalman Filter algorithm uses maximum likelihood method. In this way, the Kalman Filter algorithm can be used with the maximum likelihood in the time domain to estimate the parameters of the TVP model and the state vector

Item Type:	Conference or Workshop Item (Speech)
Additional Information:	http://jurnal.fmipa.unila.ac.id/snsmap/article/view/2498
Subjects:	H Social Sciences > HA Statistics
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika
Depositing User:	DR. KHOIRIN NISA
Date Deposited:	27 May 2020 08:08
Last Modified:	27 May 2020 08:08
URI:	http://repository.lppm.unila.ac.id/id/eprint/20703

Available Versions of this Item

• Pendugaan Model Time Varying Parameter Menggunakan Algoritma Kalman Filter. (deposited 04 Nov 2019 08:14)
  • Pendugaan Model Time Varying Parameter Menggunakan Algoritma Kalman Filter. (deposited 26 May 2020 09:00)
    • Pendugaan Model Time Varying Parameter Menggunakan Algoritma Kalman Filter. (deposited 27 May 2020 12:18)
      • Pendugaan Model Time Varying Parameter Menggunakan Algoritma Kalman Filter. (deposited 28 May 2020 07:20)
    • Pendugaan Model Time Varying Parameter Menggunakan Algoritma Kalman Filter. (deposited 27 May 2020 08:08) [Currently Displayed]

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