Consistency of trigonometric and polynomial regression estimators
نویسندگان
چکیده
منابع مشابه
Uniform in bandwidth consistency of local polynomial regression function estimators
We generalize a method for proving uniform in bandwidth consistency results for kernel type estimators developed by the two last named authors. Such results are shown to be useful in establishing consistency of local polynomial estimators of the regression function.
متن کاملLocal Polynomial Regression Estimators in Survey Sampling
Estimation of finite population totals in the presence of auxiliary information is considered. A class of estimators based on local polynomial regression is proposed. Like generalized regression estimators, these estimators are weighted linear combinations of study variables, in which the weights are calibrated to known control totals, but the assumptions on the superpopulation model are consid...
متن کاملConsistency of Bayes Estimators of a Binary Regression Function
When do nonparametric Bayesian procedures “overfit?” To shed light on this question, we consider a binary-regression problem in detail and establish frequentist consistency for a large class of Bayes procedures based on certain heirarchical priors, called uniform mixture priors. These are defined as follows: let ν be any probability distribution on the nonnegative integers. To sample a function...
متن کاملWhen Is a Trigonometric Polynomial Not a Trigonometric Polynomial?
for some nonnegative integer k and complex numbers a0, . . . , ak, b1, . . . , bk ∈ C. Trigonometric polynomials and their series counterparts, the Fourier series, play an important role in many areas of pure and applied mathematics and are likely to be quite familiar to the reader. When reflecting on the terminology, however, it is reasonable to wonder why the term trigonometric polynomial is ...
متن کاملConsistency for Least Squares Regression Estimators with Infinite Variance Data
The least squares estimators are discussed for the linear regression model with random predictors. Both predictors and errors may have infinite variance. Under the condition that the predictors are in a stable domain of attraction, we determine necessary and sufficient conditions for weak consistency of the least squares estimators in the simple linear model. The conditions vary, depending on w...
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: Applicationes Mathematicae
سال: 1998
ISSN: 1233-7234,1730-6280
DOI: 10.4064/am-25-1-73-83