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.

引用

页码：359 / 373

页数：15

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