An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies

Rabi Bhattacharya; Lizhen Lin

doi:10.1016/j.spl.2010.08.024

An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies

Rabi Bhattacharya, Lizhen Lin

Mathematics

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

We present a novel nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages. The asymptotic theory for the methodology is derived, showing that the MISEs (mean integrated squared error) of the estimates of both the dose-response curve F and its inverse F-1 achieve the optimal rate O(N^-4/5). Also, we compute the asymptotic distribution of the estimate ζ̃_p of the effective dosage ζp=F^-1(p) which is shown to have an optimally small asymptotic variance.

Original language	English (US)
Pages (from-to)	1947-1953
Number of pages	7
Journal	Statistics and Probability Letters
Volume	80
Issue number	23-24
DOIs	https://doi.org/10.1016/j.spl.2010.08.024
State	Published - Dec 2010

Keywords

Asymptotic normality
Benchmark analysis
Effective dosage
Mean integrated square error
Monotone dose-response curve estimation

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2010.08.024

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title = "An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies",

abstract = "We present a novel nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages. The asymptotic theory for the methodology is derived, showing that the MISEs (mean integrated squared error) of the estimates of both the dose-response curve F and its inverse F-1 achieve the optimal rate O(N-4/5). Also, we compute the asymptotic distribution of the estimate {\~ζ}p of the effective dosage ζp=F-1(p) which is shown to have an optimally small asymptotic variance.",

keywords = "Asymptotic normality, Benchmark analysis, Effective dosage, Mean integrated square error, Monotone dose-response curve estimation",

author = "Rabi Bhattacharya and Lizhen Lin",

year = "2010",

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T1 - An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies

AU - Bhattacharya, Rabi

AU - Lin, Lizhen

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N2 - We present a novel nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages. The asymptotic theory for the methodology is derived, showing that the MISEs (mean integrated squared error) of the estimates of both the dose-response curve F and its inverse F-1 achieve the optimal rate O(N-4/5). Also, we compute the asymptotic distribution of the estimate ζ̃p of the effective dosage ζp=F-1(p) which is shown to have an optimally small asymptotic variance.

AB - We present a novel nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages. The asymptotic theory for the methodology is derived, showing that the MISEs (mean integrated squared error) of the estimates of both the dose-response curve F and its inverse F-1 achieve the optimal rate O(N-4/5). Also, we compute the asymptotic distribution of the estimate ζ̃p of the effective dosage ζp=F-1(p) which is shown to have an optimally small asymptotic variance.

KW - Asymptotic normality

KW - Benchmark analysis

KW - Effective dosage

KW - Mean integrated square error

KW - Monotone dose-response curve estimation

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DO - 10.1016/j.spl.2010.08.024

M3 - Article

AN - SCOPUS:77958475688

SN - 0167-7152

VL - 80

SP - 1947

EP - 1953

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

IS - 23-24

ER -

An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies

Abstract

Keywords

ASJC Scopus subject areas

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