0000000000388516

AUTHOR

Juha Heikkinen

showing 2 related works from this author

Bayesian Smoothing in the Estimation of the Pair Potential Function of Gibbs Point Processes

1999

A flexible Bayesian method is suggested for the pair potential estimation with a high-dimensional parameter space. The method is based on a Bayesian smoothing technique, commonly applied in statistical image analysis. For the calculation of the posterior mode estimator a new Monte Carlo algorithm is developed. The method is illustrated through examples with both real and simulated data, and its extension into truly nonparametric pair potential estimation is discussed.

Statistics and ProbabilityMathematical optimizationposterior mode estimatorMarkov chain Monte Carlo methodsMonte Carlo methodBayesian probabilityRejection samplingEstimatorMarkov chain Monte CarloBayesian smoothingGibbs processesHybrid Monte Carlosymbols.namesakeMarquardt algorithmsymbolspair potential functionPair potentialAlgorithmMathematicsGibbs samplingBernoulli
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Fully Bayesian Approach to Image Restoration with an Application in Biogeography

1994

SUMMARY A common method of studying biogeographical ranges is an atlas survey, in which the research area is divided into a square grid and the data consist of the squares where observations occur. Often the observations form only an incomplete map of the true range, and a method is required to decide whether the blank squares indicate true absence or merely a lack of study there. This is essentially an image restoration problem, but it has properties that make the common empirical Bayesian procedures inadequate. Most notably, the observed image is heavily degraded, causing difficulties in the estimation of spatial interaction, and the assessment of reliability of the restoration is emphasi…

Statistics and ProbabilitySquare tilingAtlas (topology)Spatial interactionBayesian probabilityCommon methodcomputer.software_genreBlankGeographyData miningStatistics Probability and UncertaintySpatial analysiscomputerImage restorationApplied Statistics
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