Size-biased random closed sets

M.N.M. Lieshout, van

doi:10.1016/S0031-3203(99)00025-4

Size-biased random closed sets

M.N.M. Lieshout, van

Research output: Contribution to journal › Article › Academic › peer-review

4 Citations (Scopus)

1 Downloads (Pure)

Abstract

We indicate how granulometries may be useful in the analysis of random sets. We define a suitable size distribution function as a tool in exploratory data analysis and give a new Hanisch style estimator for it. New Markov random sets are constructed which favour certain sizes above others. A size-biased random set model is fitted to a data set concerning the incidence of heather (Diggle, Biometrics 37 (1981) 531–539).

Original language	English
Pages (from-to)	1631-1644
Number of pages	14
Journal	Pattern Recognition
Volume	32
Issue number	9
DOIs	https://doi.org/10.1016/S0031-3203(99)00025-4
Publication status	Published - 1999

Access to Document

10.1016/S0031-3203(99)00025-4

Cite this

@article{727d06f5b71647cebefbf4522da432e2,

title = "Size-biased random closed sets",

abstract = "We indicate how granulometries may be useful in the analysis of random sets. We define a suitable size distribution function as a tool in exploratory data analysis and give a new Hanisch style estimator for it. New Markov random sets are constructed which favour certain sizes above others. A size-biased random set model is fitted to a data set concerning the incidence of heather (Diggle, Biometrics 37 (1981) 531–539).",

author = "{Lieshout, van}, M.N.M.",

year = "1999",

doi = "10.1016/S0031-3203(99)00025-4",

language = "English",

volume = "32",

pages = "1631--1644",

journal = "Pattern Recognition",

issn = "0031-3203",

publisher = "Elsevier",

number = "9",

}

TY - JOUR

T1 - Size-biased random closed sets

AU - Lieshout, van, M.N.M.

PY - 1999

Y1 - 1999

N2 - We indicate how granulometries may be useful in the analysis of random sets. We define a suitable size distribution function as a tool in exploratory data analysis and give a new Hanisch style estimator for it. New Markov random sets are constructed which favour certain sizes above others. A size-biased random set model is fitted to a data set concerning the incidence of heather (Diggle, Biometrics 37 (1981) 531–539).

AB - We indicate how granulometries may be useful in the analysis of random sets. We define a suitable size distribution function as a tool in exploratory data analysis and give a new Hanisch style estimator for it. New Markov random sets are constructed which favour certain sizes above others. A size-biased random set model is fitted to a data set concerning the incidence of heather (Diggle, Biometrics 37 (1981) 531–539).

U2 - 10.1016/S0031-3203(99)00025-4

DO - 10.1016/S0031-3203(99)00025-4

M3 - Article

SN - 0031-3203

VL - 32

SP - 1631

EP - 1644

JO - Pattern Recognition

JF - Pattern Recognition

IS - 9

ER -

Size-biased random closed sets

Abstract

Access to Document

Fingerprint

Cite this