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A New Test in Parametric Linear Models against Nonparametric Autoregressive Errors
Gao, Jiti; King, Maxwell - Department of Econometrics and Business Statistics, … - 2011
This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is proposed and studied to deal with the parametric specification of the nonparametric autoregressive errors with either stationarity or nonstationarity. Such a test procedure can initially...
Persistent link: https://www.econbiz.de/10009318804
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Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series
Gao, Jiti; Li, Degui; Tjøstheim, Dag - Department of Econometrics and Business Statistics, … - 2011
This paper establishes a suite of uniform consistency results for nonparametric kernel density and regression estimators when the time series regressors concerned are nonstationary null-recurrent Markov chains. Under suitable conditions, certain rates of convergence are also obtained for the...
Persistent link: https://www.econbiz.de/10009318806
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Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates
Li, Degui; Lu, Zudi; Linton, Oliver - Department of Econometrics and Business Statistics, … - 2011
Local linear fitting is a popular nonparametric method in statistical and econometric modelling. Lu and Linton (2007) established the pointwise asymptotic distribution for the local linear estimator of a nonparametric regression function under the condition of near epoch dependence. In this...
Persistent link: https://www.econbiz.de/10009318809
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Estimation in threshold autoregressive models with a stationary and a unit root regime
Gao, Jiti; Tjøstheim, Dag; Yin, Jiying - Department of Econometrics and Business Statistics, … - 2011
This paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a … we consider, and nonstandard estimation problems are the result. This paper proposes a parameter estimation method for …/4, whereas it is n-1 in the nonstationary regime. The proposed theory and estimation method are illustrated by both simulated …
Persistent link: https://www.econbiz.de/10009318810
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Nonparametric modeling and forecasting electricity demand: an empirical study
Shang, Han Lin - Department of Econometrics and Business Statistics, … - 2010
This paper uses half-hourly electricity demand data in South Australia as an empirical study of nonparametric modeling and forecasting methods for prediction from half-hour ahead to one year ahead. A notable feature of the univariate time series of electricity demand is the presence of both...
Persistent link: https://www.econbiz.de/10008725785
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Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models
Ng, Jason; Forbes, Catherine S.; Martin, Gael M.; … - Department of Econometrics and Business Statistics, … - 2011
The object of this paper is to produce non-parametric maximum likelihood estimates of forecast distributions in a general non-Gaussian, non-linear state space setting. The transition densities that define the evolution of the dynamic state process are represented in parametric form, but the...
Persistent link: https://www.econbiz.de/10009291983
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An Improved Nonparametric Unit-Root Test
Gao, Jiti; King, Maxwell - Department of Econometrics and Business Statistics, … - 2012
This paper proposes a simple and improved nonparametric unit-root test. An asymptotic distribution of the proposed test is established. Finite sample comparisons with an existing nonparametric test are discussed. Some issues about possible extensions are outlined.
Persistent link: https://www.econbiz.de/10010860412
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Nonparametric Regression Approach to Bayesian Estimation
Gao, Jiti; Hong, Han - Department of Econometrics and Business Statistics, … - 2014
Estimation of unknown parameters and functions involved in complex nonlinear econometric models is a very important … issue. Existing estimation methods include generalised method of moments (GMM) by Hansen (1982) and others, efficient method …), and nonparametric simulated maximum likelihood estimation (NSMLE) method by Creel and Kristensen (2011), and Kristensen …
Persistent link: https://www.econbiz.de/10011093868
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Expansion of Lévy Process Functionals and Its Application in Statistical Estimation
Dong, Chaohua; Gao, Jiti - Department of Econometrics and Business Statistics, … - 2012
In this paper, expansions of functionals of Lévy processes are established under some Hilbert spaces and their orthogonal bases. From practical standpoint, both time-homogeneous and time-inhomogeneous functionals of Lévy processes are considered. Several expansions and rates of convergence are...
Persistent link: https://www.econbiz.de/10009650287
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Boosting multi-step autoregressive forecasts
Taieb, Souhaib Ben; Hyndman, Rob J - Department of Econometrics and Business Statistics, … - 2014
estimation variance over the forecast horizon. Using a nonlinear machine learning model makes the tradeoff even more difficult …
Persistent link: https://www.econbiz.de/10010958944