Steepest descent algorithms in a space of measures

被引：24

作者：

Molchanov, I

Zuyev, S

机构：

[1] Univ Glasgow, Dept Stat, Glasgow G12 8QW, Lanark, Scotland

[2] Univ Strathclyde, Dept Stat & Modelling Sci, Glasgow G1 1XH, Lanark, Scotland

来源：

STATISTICS AND COMPUTING | 2002年 / 12卷 / 02期

关键词：

gradient methods; steepest descent; k-means; P-means; optimal experimental design; Poisson process; Boolean model; Splus; R;

D O I：

10.1023/A:1014878317736

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The paper describes descent type algorithms suitable for solving optimisation problems for functionals that depend on measures. We mention several examples of such problems that appear in optimal design, cluster analysis and optimisation of spatial distribution of coverage processes.

引用

页码：115 / 123

页数：9

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