Time series extrinsic regression

Regression Quantiles for Time Series

In this article we study nonparametric estimation of regression quantiles by inverting a weighted Nadaraya-Watson estimator (WNW) of conditional distribution function, which was rst used by Hall, Woll and Yao (1999). First, under some regularity conditions, we establish the asymptotic normality and weak consistency of the WNW conditional distribution estimator for-mixing time series at both bou...

Regression Models for Time Series Analysis

Nonparametric regression for locally stationary time series

In this paper, we study nonparametric models allowing for locally stationary regressors and a regression function that changes smoothly over time. These models are a natural extension of time series models with time-varying coefficients. We introduce a kernel-based method to estimate the time-varying regression function and provide asymptotic theory for our estimates. Moreover, we show that the...

Multiple Time Series Regression with Integrated Processes

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Confidence Bands in Nonparametric Time Series Regression

We consider nonparametric estimation of mean regression and conditional variance (or volatility) functions in nonlinear stochastic regression models. Simultaneous confidence bands are constructed and the coverage probabilities are shown to be asymptotically correct. The imposed dependence structure allows applications in many linear and nonlinear auto-regressive processes. The results are appli...