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Image‐Based Empirical Importance Sampling: An Efficient Way of Estimating Intensities
Author(s) -
HANSEN LINDA V.,
KIDERLEN MARKUS,
VEDEL JENSEN EVA B.
Publication year - 2011
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2010.00725.x
Subject(s) - estimator , sampling (signal processing) , mathematics , point process , construct (python library) , statistics , stochastic process , mathematical optimization , algorithm , computer science , computer vision , filter (signal processing) , programming language
. Very recently, it has been suggested in the biomedical literature to combine computerized image analysis with non‐uniform sampling to increase the efficiency of estimators of intensities of biological cell populations. We give this ingenious idea of empirical importance sampling a stochastic formulation, using point process theory and modern sampling theory. We develop statistical tools for assessing its efficiency and construct optimal model‐based estimators of intensities. Examples of applications of empirical importance sampling in microscopy are provided.