Decompounding random sums: a nonparametric approach

DOI10.1007/s10463-008-0200-6zbMath1432.60049OpenAlexW2041896754MaRDI QIDQ907021

Susan M. Pitts, Martin Bøgsted

Publication date: 1 February 2016

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: http://vbn.aau.dk/ws/files/3617270/R-2006-20.pdf

zbMATH Keywords

functional central limit theoremasymptotic normalityinverse problemsempirical processesdecompoundingcompound distributionsinfinite-dimensional delta method

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Characteristic functions; other transforms (60E10) Sums of independent random variables; random walks (60G50) Functional limit theorems; invariance principles (60F17)

Related Items (7)

Estimation of the Jump Size Density in a Mixed Compound Poisson Process ⋮ Statistical inference across time scales ⋮ Weighted empirical processes in the nonparametric inference for Lévy processes ⋮ Probabilistic sampling of finite renewal processes ⋮ A note on recovering the distributions from exponential moments ⋮ Maxentropic approach to decompound aggregate risk losses ⋮ Efficient nonparametric inference for discretely observed compound Poisson processes

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