Higher-order expansions of sample extremal quotient from skew-normal distribution

Consider the sequence {Xn,n≥1} of independent random variables, sharing an identical skew-normal distribution, and define Mn and mn as the partial maximum and minimum of the sequence. This paper establishes the limiting distribution of the normalized sample extremal quotient mn/Mn. With appropriate normalizing constants, we derive higher-order asymptotic expansions for the distribution of normalized sample extremal quotient, from which the associated convergence rate to its limiting distribution is obtained. Numerical analysis is provided to compare the accuracy of different asymptotics.

Authors

Institutions

Publication Details

Journal
Communication in Statistics- Theory and Methods
Published
2026-09-10
DOI
https://doi.org/10.1080/03610926.2026.2729398
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Higher-order expansions of sample extremal quotient from skew-normal distribution

Yechen Wu
Communication in Statistics- Theory and Methods
Statistical Distribution Estimation and Applications
article

Higher-order expansions of sample extremal quotient from skew-normal distribution

Yechen Wu
article en

Abstract

Consider the sequence {Xn,n≥1} of independent random variables, sharing an identical skew-normal distribution, and define Mn and mn as the partial maximum and minimum of the sequence. This paper establishes the limiting distribution of the normalized sample extremal quotient mn/Mn. With appropriate normalizing constants, we derive higher-order asymptotic expansions for the distribution of normalized sample extremal quotient, from which the associated convergence rate to its limiting distribution is obtained. Numerical analysis is provided to compare the accuracy of different asymptotics.

Communication in Statistics- Theory and Methods
Southwest University (CN)
Openalex Percentile: Top 7%
Statistical Distribution Estimation and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.