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ЖУРНАЛЫ // Theory of Stochastic Processes // Архив

Theory Stoch. Process., 2007, том 13(29), выпуск 2, страницы 316–327 (Mi thsp208)

On local linear estimation in nonparametric errors-in-variables models

Silvelyn  Zwanzig

Department of Mathematics, Uppsala University, SE-75106 Uppsala, Box 480 Sweden

Аннотация: Local linear methods are applied to a nonparametric regression model with normal errors in the variables and uniform distribution of the variables. The local neighborhood is determined with help of deconvolution kernels. Two different linear estimation method are used: the naive estimator and the total least squares estimator. Both local linear estimators are consistent. But only the local naive estimator delivers an estimation of the tangent.

Ключевые слова: Error in variable, measurement errors, nonparametric regression, deconvolution, kernel methods, local linear regression, naive estimation, total least squares.

MSC: 62G08, 62G05, 62G20

Язык публикации: английский



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