INAR(1) MODEL WITH POISSON DIFFERENCE MARGINAL DISTRIBUTION
Prediction of future observations for discrete random variable may be modeled by Integer-Valued Autoregressive or INAR. The interpretation of such model is described as follows: number of individuals at certain time is the sum of number of individuals who have survived (survivors) and number of a...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/33869 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Prediction of future observations for discrete random variable may be modeled
by Integer-Valued Autoregressive or INAR. The interpretation of such model is
described as follows: number of individuals at certain time is the sum of number
of individuals who have survived (survivors) and number of arrivals. INAR model
is mainly built by involving a thinning operator \ as well as certain discrete distribution
for innovation. Some common distributions are usually employed such as
Poisson and Geometric distributions. This book propose an INAR(1) model with
Poisson Dierence (PD) marginal distribution. PD distribution is developed as the
distribution of the dierence of two Poisson random variables. This model, called
PD-INAR(1), is motivated by the need to accommodate negative values of the data.
Parameter estimation techniques used for the model are the methods of moment
and maximum likelihood. Meanwhile, a Monte Carlo simulation is carried out to
illustrate some properties of the model. |
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