On the asymptotic normality of frequency polygons for strongly mixing spatial processes

Mohamed El Machkouri ()

Statistical Inference for Stochastic Processes, 2013, vol. 16, issue 3, 193-206

Abstract: This paper establishes the asymptotic normality of frequency polygons in the context of stationary strongly mixing random fields indexed by $$\mathbb {Z}^d$$ Z d . Our method allows us to consider only minimal conditions on the width bins and provides a simple criterion on the mixing coefficients. In particular, we improve in several directions a previous result by Carbon, Francq and Tran 2010 . Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Central limit theorem; Spatial processes; Random fields; Nonparametric density estimation; Frequency polygon; Histogram; Mixing; 62G05; 62G07; 60G60 (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sistpr:v:16:y:2013:i:3:p:193-206

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DOI: 10.1007/s11203-013-9086-x

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