Multivariate Local Polynomial Regression with Application to Shenzhen Component Index

Multivariate Local Polynomial Regression with Application to Shenzhen Component Index

This study attempts to characterize and predict stock index series in Shenzhen stock market using the concepts of multivariate local polynomial regression. Based on nonlinearity and chaos of the stock index time series, multivariate local polynomial prediction methods and univariate local polynomial prediction method, all of which use the concept of phase space reconstruction according to Taken...

Multivariate Regression Estimation : Local Polynomial Fitting for Time Series

We consider the estimation of the multivariate regression function m (x 1 , . . . ,xd) = E [ψ (Yd) | X 1 = x 1 , . . . ,Xd = xd], and its partial derivatives, for stationary random processes {Yi ,Xi} using local higher-order polynomial fitting. Particular cases of ψ yield estimation of the conditional mean, conditional moments and conditional distributions. Joint asymptotic normality is establi...

The Application of Local Polynomial Regression to Survey Sampling Estimation

A new class of model-assisted estimators based on local polynomial regression is suggested. The estimators are weighted linear combinations of study variables, in which the weights are calibrated to known control totals. The es-timators are asymptotically design-unbiased and consistent under mild assumptions , and we provide a consistent estimator for the design mean squared error. Bandwidth se...

Multivariate calibration with single-index signal regression

Article history: In general, linearity is assum Received 16 November 2008 Received in revised form 20 January 2009 Accepted 3 February 2009 Available online 12 February 2009

Local Polynomial Regression