Density testing in a contaminated sample

DOI10.1016/j.jmva.2005.09.010zbMath1102.62045OpenAlexW2068523437MaRDI QIDQ860334

Nicolai Bissantz, Hajo Holzmann, Axel Munk

Publication date: 9 January 2007

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2005.09.010

zbMATH Keywords

asymptotic normalitysimulationsdeconvolutionintegrated square errorgoodness of fitcomposite hypothesesmultivariate nonparametric density estimation

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15)

Related Items (17)

Adaptive goodness-of-fit testing from indirect observations ⋮ Goodness-of-fit tests in linear EV regression with replications ⋮ Model Checks in Inverse Regression Models with Convolution-Type Operators ⋮ Multiscale methods for shape constraints in deconvolution: confidence statements for qualitative features ⋮ Testing inverse problems: a direct or an indirect problem? ⋮ Adaptivity in convolution models with partially known noise distribution ⋮ Goodness-of-fit test for noisy directional data ⋮ Testing for Lack of Fit in Inverse Regression—with Applications to Biophotonic Imaging ⋮ Nonparametric specification tests for stochastic volatility models based on volatility density ⋮ Multiscale scanning in inverse problems ⋮ Goodness-of-fit testing strategies from indirect observations ⋮ Testing parametric models in the presence of instrumental variables ⋮ On testing for local monotonicity in deconvolution problems ⋮ SPECIFICATION TESTING FOR ERRORS-IN-VARIABLES MODELS ⋮ Goodness-of-fit testing of error distribution in linear measurement error models ⋮ Local bandwidth selectors for deconvolution kernel density estimation ⋮ Data driven smooth test for contaminated data

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