Asymptotic properties of local polynomial regression with missing data and correlated errors
نویسندگان
چکیده
منابع مشابه
Wavelet Threshold Estimator of Semiparametric Regression Function with Correlated Errors
Wavelet analysis is one of the useful techniques in mathematics which is used much in statistics science recently. In this paper, in addition to introduce the wavelet transformation, the wavelet threshold estimation of semiparametric regression model with correlated errors with having Gaussian distribution is determined and the convergence ratio of estimator computed. To evaluate the wavelet th...
متن کاملA Plug-in Bandwidth Selector for Local Polynomial Regression Estimator with Correlated Errors
Consider the Þxed regression model where the error random variables are coming from a strictly stationary, non-white noise stochastic process. In a situation like this, automated bandwidth selection methods for nonparametric regression break down. We present a plug-in method for choosing the smoothing parameter for local least squares estimators of the regression function. The method takes the ...
متن کاملNonparametric Regression with Correlated Errors
Nonparametric regression techniques are often sensitive to the presence of correlation in the errors. The practical consequences of this sensitivity are explained, including the breakdown of several popular data-driven smoothing parameter selection methods. We review the existing literature in kernel regression, smoothing splines and wavelet regression under correlation, both for short-range an...
متن کاملKernel Regression with Correlated Errors
It is a well-known problem that obtaining a correct bandwidth in nonparametric regression is difficult in the presence of correlated errors. There exist a wide variety of methods coping with this problem, but they all critically depend on a tuning procedure which requires accurate information about the correlation structure. Since the errors cannot be observed, the latter is a hard goal to achi...
متن کاملRegression models for high-dimensional data with correlated errors
where y is the n× 1 response vector; X is an n× p model matrix representing the predictors; and β is a p × 1 vector of coefficients to estimate. For mathematical simplicity, it is typical to set the first predictor as the intercept β0 so that the first column of X is the n×1 vector of ones. The intercept acts as a sink for the mean effect of included predictors, so one could remove the intercep...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Annals of the Institute of Statistical Mathematics
سال: 2007
ISSN: 0020-3157,1572-9052
DOI: 10.1007/s10463-007-0136-2