estimation of the error density in a semiparametric transformation model Bloomingdale, Ohio

Part of Springer Nature. Subjects: Statistics Theory (math.ST) Citeas: arXiv:1110.1846 [math.ST] (or arXiv:1110.1846v1 [math.ST] for this version) Submission history From: Rawane Samb [view email] [v1] Sun, 9 Oct 2011 14:57:23 GMT (21kb) Which authors doi:10.1007/s10463-013-0441-x 166 Views AbstractConsider the semiparametric transformation model $$\Lambda _{\theta _o}(Y)=m(X)+\varepsilon$$, where $$\theta _o$$ is an unknown finite dimensional parameter, the functions $$\Lambda _{\theta _o}$$ and $$m$$ are smooth, \(\varepsilon Mathematical Reviews (MathSciNet): MR2333499 Digital Object Identifier: doi:10.1111/j.1468-0262.2007.00787.x Zentralblatt MATH: 1134.91548Linton, O.

Statist. Ann. Bernoulli 8 607–625. Mathematical Reviews (MathSciNet): MR624332 Digital Object Identifier: doi:10.2307/2287831 JSTOR: links.jstor.org Zentralblatt MATH: 0464.62058Box, G.

EconPapers is hosted by the Örebro University School of Business. P. (1999). Journal of Econometrics, 167, 305–316.Fitzenberger, B., Wilke, R. J.

Journal of Nonparametric Statistics, 7, 279–293.Akritas, M. and Cox, D. The small sample performance is studied in several simulations. J. (1992).

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This book demonstrates the application of mathematics to research topics in ecology and environmental science, health and medicine, phylogenetics and neural networks, theoretical chemistry, economics and management. Biometrika 82 93–100. B. L. (1998).

First the problem of identification of such models is discussed. Statistics and Probability Letters, 78, 50–59.Dette, H., Kusi-Appiah, S., Neumeyer, N. (2002). Optimal rates of convergence for nonparametric estimators. Estimation of semiparametric models when the criterion function is not smooth.

An analysis of transformations revisited. Here is how to contribute. and Van Der Vaart, Aad W., Bernoulli, 1999On differentiability of implicitly defined function in semi-parametric profile likelihood estimationHirose, Yuichi, Bernoulli, 2016A semi-parametric model for censored and passively registered dataJonker, Marianne A. P., Linton, O.

B., Chen, R., Wang, N. By using our services, you agree to our use of cookies.Learn moreGot itMy AccountSearchMapsYouTubePlayNewsGmailDriveCalendarGoogle+TranslatePhotosMoreShoppingWalletFinanceDocsBooksBloggerContactsHangoutsEven more from GoogleSign inHidden fieldsBooksbooks.google.com - The construction of mathematical models is an essential scientific activity. Uniform in bandwidth consistency of kernel-type function estimators. Theory of Probability and its Applications, 9, 141–142.Neumeyer, N., Dette, H. (2007).

Volume 36, Number 2 (2008), 686-718.Estimation of a semiparametric transformation modelOliver Linton, Stefan Sperlich, and Ingrid Van Keilegom More by Oliver LintonSearch this author in:Google ScholarProject Euclid More by Stefan SperlichSearch Springer, New York. Assoc. 92 1512–1521. Statist. 27 1443–1490.

You have partial access to this content. Ann. Annals of Statistics, 33, 1380–1403.Escanciano, J. Econometrica 64 891–916.

P., Cox, D. We propose a kernel-type estimator of the density of the error $$\varepsilon$$ ε , and prove its asymptotic normality. Comptes Rendus de l’Académie des Sciences-Paris, Série I, 349, 1281–1285.Shin, Y. (2008). Assoc. 76 296–311.

Testing symmetry of an unknown density function by kernel method. On estimating regression. Statist. Mathematical Reviews (MathSciNet): MR1014890 Zentralblatt MATH: 0666.62062Chen, X., Linton, O.

Testing for symmetric error distribution in nonparametric regression models. L. (1996). R. (1964). Nonparametric estimation of a generalized additive model with an unknown link function.

Soc. The system returned: (22) Invalid argument The remote host or network may be down. and Van Keilegom, I. (2003). and Wellner, J.