SIMULATION PROCEDURES AND LIKELIHOOD INFERENCE FOR SPATIAL POINT-PROCESSES

被引：0
|
作者：
GEYER, CJ [1 ]
MOLLER, J [1 ]
机构：
[1] AARHUS UNIV,INST MATH,DEPT THEORET STAT,DK-8000 AARHUS C,DENMARK
来源：
SCANDINAVIAN JOURNAL OF STATISTICS | 1994年 / 21卷 / 04期
关键词：
CONDITIONAL MAXIMUM LIKELIHOOD; GIBBSIAN POINT PROCESSES; MARKOV CHAIN MONTE CARLO; METROPOLIS-HASTINGS ALGORITHMS; SPATIAL BIRTH-AND-DEATH PROCESSES; STRAUSS PROCESS; UNCONDITIONAL MAXIMUM;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
An alternative algorithm to the usual birth-and-death procedure for simulating spatial point processes is introduced. The algorithm is used in a discussion of unconditional versus conditional likelihood inference for parametric models of spatial point processes.
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页码：359 / 373
页数：15
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