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  <title>Pedekatan Bayesian Dalam Penaksiran Parameter Pada Model Hidden Markov</title>
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  <namePart>Dwi Agustin Nuriani Sirodj</namePart>
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   <placeTerm type="text">Bandung</placeTerm>
   <publisher>Magister Statistika Terapan</publisher>
   <dateIssued>2012</dateIssued>
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  <languageTerm type="text">Indonesia</languageTerm>
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 <note>Tesis ini menyajikan sebuah kajian mengenai penaksiran parameter dalam &#13;
hidden markov model. Pendekatan yang dilakukan adalah pendekatan bayesian &#13;
dimana,akan terdapat dua buah sumber informasi, yaitu informasi dari fungsi &#13;
lilcelihood dan informasi dari fungsi prior. Pendekatan ini akan diaplikasikan &#13;
pada data curah hujan harian di Darajat, Garut. Banyaknya status hidden yang &#13;
akan digunakan adalah tiga buah status sesuai dengan klasifikasi iklim &#13;
berdasarkan klasifikasi Schmidth dan Fergusson yang memang cocok dipakai &#13;
untuk kondisi daerah tersebut. Algoritma yang digunakan dalarn proses simulasi &#13;
penaksiran parameter yaitu algoritma Gibbs Sampler. &#13;
&#13;
10. Abstract &#13;
&#13;
This paper presents study about the parameter estimation in hidden markov &#13;
model. The approach is taken from a Bayesian method, there will be two sources of &#13;
information, they are information from the likelihood function and the prior function. &#13;
This approach will be applied to daily rainfall data in Darajat, Garut. The number &#13;
of hidden state are used in this paper consist of three kind of climate states based &#13;
on Schmidth and Fergusson's climate classification which are suitable to the local &#13;
conditions. The algorithm that used in the simulation process of parameter &#13;
estimation is Gibbs Sampler algorithm.</note>
 <note type="statement of responsibility">Dwi Agustin Nuriani Sirodj</note>
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  <topic>Pendekatan Bayesian Dalam Penaksiran Parameter  Pa</topic>
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