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pro vyhledávání: '"Chown, Justin"'
In this paper we investigate an indirect regression model characterized by the Radon transformation. This model is useful for recovery of medical images obtained by computed tomography scans. The indirect regression function is estimated using a seri
Externí odkaz:
http://arxiv.org/abs/1902.03418
We propose a goodness-of-fit test for the distribution of errors from a multivariate indirect regression model. The test statistic is based on the Khmaladze transformation of the empirical process of standardized residuals. This goodness-of-fit test
Externí odkaz:
http://arxiv.org/abs/1812.02409
We propose completely nonparametric methodology to investigate location-scale modelling of two-component mixture cure models, where the responses of interest are only indirectly observable due to the presence of censoring and the presence of so-calle
Externí odkaz:
http://arxiv.org/abs/1803.03512
Publikováno v:
Statistica Sinica, 2020 Jan 01. 30(3), 1255-1283.
Externí odkaz:
https://www.jstor.org/stable/26968928
Autor:
Chown, Justin, Müller, Ursula U.
Heteroskedastic errors can lead to inaccurate statistical conclusions if they are not properly handled. We introduce a test for heteroskedasticity for the nonparametric regression model with multiple covariates. It is based on a suitable residual-bas
Externí odkaz:
http://arxiv.org/abs/1610.09139
Autor:
Chown, Justin
Publikováno v:
Statist. Probab. Lett. 117, 31-39 (2016)
A residual-based empirical distribution function is proposed to estimate the distribution function of the errors of a heteroskedastic nonparametric regression with responses missing at random based on completely observed data, and this estimator is s
Externí odkaz:
http://arxiv.org/abs/1610.08768
Residual-based analysis is generally considered a cornerstone of statistical methodology. For a special case of indirect regression, we investigate the residual-based empirical distribution function and provide a uniform expansion of this estimator,
Externí odkaz:
http://arxiv.org/abs/1610.08663
Autor:
Chown, Justin, Müller, Ursula U.
Publikováno v:
Chown, J. and M\"uller, U.U. (2013). Efficiently estimating the error distribution in nonparametric regression with responses missing at random. J. Nonparametr. Stat. 25, 665-677
This article considers nonparametric regression models with multivariate covariates and with responses missing at random. We estimate the regression function with a local polynomial smoother. The residual-based empirical distribution function that on
Externí odkaz:
http://arxiv.org/abs/1610.08360
Autor:
Chown, Justin, Müller, Ursula U.
Publikováno v:
Journal of the Royal Statistical Society. Series B (Statistical Methodology), 2019 Jan 01. 81(4), 805-806.
Externí odkaz:
https://www.jstor.org/stable/26773235
Autor:
Chown, Justin, Müller, Ursula U.
Publikováno v:
Journal of the Royal Statistical Society. Series B (Statistical Methodology), 2018 Jan 01. 80(5), 951-974.
Externí odkaz:
https://www.jstor.org/stable/26773188