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A local linear estimator of generalized impulse response (GIR) functions for nonlinear conditional heteroskedastic autoregressive processes is derived and shown to be asymptotically normal. A plug-in bandwidth is obtained that minimizes the asymptotical mean squared error of the GIR estimator. A...
Persistent link: https://www.econbiz.de/10010956384
Optimal bandwidths for local polynomial regression usually involve functionals of the derivatives of the unknown regression function. In the multivariate case, estimates of these functionals are not readily available, primarily because estimating multivariate derivatives is complicated. In this...
Persistent link: https://www.econbiz.de/10010956407
A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...
Persistent link: https://www.econbiz.de/10010956477
Persistent link: https://www.econbiz.de/10005610593
We derive a local linear estimator of generalized impulse response (GIR) functions for nonlinear conditional heteroskedastic autoregressive processes and show its asymptotic normality. We suggest a plug-in bandwidth based on the derived asymptotically optimal bandwidth. A local linear estimator...
Persistent link: https://www.econbiz.de/10005699554
The generalized additive model (GAM) is a multivariate nonparametric regression tool for non-Gaussian responses including binary and count data. We propose a spline-backfitted kernel (SBK) estimator for the component functions and the constant, which are oracally efficient under weak dependence....
Persistent link: https://www.econbiz.de/10011133912
Functional data analysis (FDA) has become an important area of statistics research in the recent decade, yet a smooth simultaneous confidence corridor (SCC) does not exist in the literature for the mean function of sparse functional data. SCC is a powerful tool for making statistical inference...
Persistent link: https://www.econbiz.de/10011133920
In spite of the widespread use of generalized additive models (GAMs), there is no well established methodology for simultaneous inference and variable selection for the components of GAM. There is no doubt that both, inference on the marginal component functions and their selection, are...
Persistent link: https://www.econbiz.de/10010734526
We consider a varying coefficient regression model for sparse functional data, with time varying response variable depending linearly on some time independent covariates with coefficients as functions of time dependent covariates. Based on spline smoothing, we propose data driven simultaneous...
Persistent link: https://www.econbiz.de/10010734528
Additive modelling has been widely used in nonparametric regression to circumvent the curse of dimensionality, by reducing the problem of estimating a multivariate regression function to the estimation of its univariate components. Estimation of these univariate functions, however, can suffer...
Persistent link: https://www.econbiz.de/10010983415