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

Research output: Contribution to journalArticle

10 Citations (Scopus)

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 ζ̃p of the effective dosage ζp=F-1(p) which is shown to have an optimally small asymptotic variance.

Original languageEnglish (US)
Pages (from-to)1947-1953
Number of pages7
JournalStatistics and Probability Letters
Volume80
Issue number23-24
DOIs
StatePublished - Dec 2010

Fingerprint

Bioassay
Nonparametric Methods
Adaptive Method
Benchmark
Dose-response Curve
Mean Integrated Squared Error
Optimal Rates
Asymptotic Variance
Asymptotic Theory
Risk Assessment
Estimate
Asymptotic distribution
Disjoint
Subgroup
Methodology
Nonparametric methods
Environmental studies
Integrated
Asymptotic theory
Asymptotic variance

Keywords

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

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

Cite this

An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies. / Bhattacharya, Rabindra N; Lin, Lizhen.

In: Statistics and Probability Letters, Vol. 80, No. 23-24, 12.2010, p. 1947-1953.

Research output: Contribution to journalArticle

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