Large and Moderate Deviation Principles for Recursive Kernel Estimators for Spatial Data

Salim Bouzebda; Yousri Slaoui

doi:10.31390/josa.1.1.07

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Large and Moderate Deviation Principles for Recursive Kernel Estimators for Spatial Data

Salim Bouzebda Yousri Slaoui

Year: 2020 Journal: Journal of Stochastic Analysis Vol: 1 (1) Publisher: Louisiana State University

DOI: 10.31390/josa.1.1.07

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Abstract

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Keywords:

Estimator Kernel (algebra) Statistics Mathematics Kernel density estimation Computer science Spatial analysis Algorithm Applied mathematics Econometrics Combinatorics

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Soil Geostatistics and Mapping

Physical Sciences → Environmental Science → Environmental Engineering

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Large and Moderate Deviation Principles for Recursive Kernel Estimators for Spatial Data

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