| dc.contributor.advisor | Setiawaty, Berlian | |
| dc.contributor.advisor | Purnaba, I Gusti Putu | |
| dc.contributor.author | Fikri, Miftahul | |
| dc.date.accessioned | 2023-06-05T06:53:32Z | |
| dc.date.available | 2023-06-05T06:53:32Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/118360 | |
| dc.description.abstract | Model hidden Markov terdiri dari sepasang proses stokastik yaitu proses observasi dan proses yang memengaruhi observasi. Proses stokastik yang memengaruhi observasi ini diasumsikan membentuk rantai Markov dan tidak diamati. Model Poisson hidden Markov (MPHM) adalah salah satu model hidden Markov diskret dan proses observasinya jika diketahui proses yang memengaruhinya diasumsikan menyebar Poisson. | id |
| dc.description.abstract | A hidden Markov model (HMM) consists of a pair of stochastic processes, that is the observation process and process that affected observation. The stochastic process which causes this observation is assumed to form a Markov chain and is not observed. Poisson hidden Markov models (PHMM) is one of the discrete HMM and the observation process given the cause is assumed having a Poisson distribution. | id |
| dc.language.iso | id | id |
| dc.publisher | IPB University | id |
| dc.subject.ddc | Mathematical model - Algorithm | id |
| dc.title | Pendugaan parameter dan kekonvergenan penduga parameter model Poisson hidden Markov | id |
| dc.title.alternative | Estimating Parameter and the Convergence of Parameter Estimator of Poisson Hidden Markov Model | id |
| dc.type | Thesis | id |
| dc.subject.keyword | Poisson hidden Markov model | id |
| dc.subject.keyword | Forward-Backward algorithm | id |
| dc.subject.keyword | Expectation Maximization algorithm | id |
