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Approximations to distributions of statistics used for testing hypotheses about the number of modes of a population

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Publication:1125975
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DOI10.1016/S0378-3758(96)00072-9zbMath0936.62043MaRDI QIDQ1125975

Andrew T. A. Wood, Hall, Peter

Publication date: 18 May 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)


zbMATH Keywords

bootstrapMonte CarlobandwidthGaussian processkernelmode


Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric hypothesis testing (62G10) Gaussian processes (60G15) Asymptotic distribution theory in statistics (62E20)


Related Items

Estimating the number of clusters



Cites Work

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  • Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems
  • The dip test of unimodality
  • Some asymptotics for multimodality tests based on kernel density estimates
  • Excess Mass Estimates and Tests for Multimodality
  • Tests for Hurst effect
  • Density Estimation and Bump-Hunting by the Penalized Likelihood Method Exemplified by Scattering and Meteorite Data
  • An approximation of partial sums of independent RV'-s, and the sample DF. I
  • Nonparametric Statistical Data Modeling
  • On Qualitative Smoothness of Kernel Density Estimates1
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