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ABSTRACT: <br /> <br /> <br /> <br /> <br /> Counting process is a stochastic process which has a discrete state space and parameter index such as time, location and both of them. The example of counting process is point processes. There 4 approaches to construct p...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/6685 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | ABSTRACT: <br />
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Counting process is a stochastic process which has a discrete state space and parameter index such as time, location and both of them. The example of counting process is point processes. There 4 approaches to construct point processes; counting measure, step function, sequence of points, and sequence of intervals. Related to the counting measure, trivial case of point processes is Poisson process, especially extended nonhomogeneous Poisson, which is characterized by an intensity function. The ilustration of intensity function is approached by analyzing maximum likelihood method, which nonhomogeneous Poisson likelihood function contains Riemann-Stieltjes integration and by using longleaf pine data at Wade Tract forest, Thomas County, Georgia. |
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