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Kernel density estimators for random fields satisfying an interlaced mixing condition
Authors:Cristina Tone
Affiliation:Department of Mathematics, University of Louisville, 328 Natural Sciences Building, Louisville, KY 40292, United States
Abstract:For a sequence of strictly stationary random fields that are uniformly ρ′-mixingρ-mixing and satisfy a Lindeberg condition, a central limit theorem is obtained for sequences of “rectangular” sums from the given random fields. The “Lindeberg CLT” is then used to prove a CLT for some kernel estimators of probability density for some strictly stationary random fields satisfying ρ′-mixingρ-mixing, and whose probability density and joint densities are absolutely continuous.
Keywords:Central limit theorem   ζ-Mixing  si0001.gif"   overflow="  scroll"  >ζ  normal"  >-Mixing   ρ&prime  -Mixing  si0002.gif"   overflow="  scroll"  >ρ&prime    normal"  >-Mixing   Random fields   Kernel-type estimator   Spectral density
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