Narrow search
Showing 41 - 50 of 118,985
Cover Image
Nonparametric regression estimation for multivariate null recurrent processes
Cai, Biqing; Tjostheim, Dag - In: Econometrics : open access journal 3 (2015) 2, pp. 265-288
proper normalization) is normal. Furthermore, we show that the two-step estimator for the volatility function is consistent …
Persistent link: https://www.econbiz.de/10011297654
Cover Image
Data-Driven Bandwidth Selection for Nonparametric Nonstationary Regressions
Bandi, Federico M. - 2011
We provide a solution to the open problem of bandwidth selection for the nonparametric estimation of potentially non-stationary regressions, a setting in which the popular method of cross-validation has not been justified theoretically. Our procedure is based on minimizing moment conditions...
Persistent link: https://www.econbiz.de/10013123167
Cover Image
Pseudo-Maximum Likelihood Estimation in Two Classes of Semiparametric Diffusion Models
Kristensen, Dennis - 2009
A novel estimation method for two classes of semiparametric scalar diffusion models is proposed: In the first class, the diffusion term is parameterised and the drift is left unspecified, while in the second class only the drift term is specified. Under the assumption of stationarity, the...
Persistent link: https://www.econbiz.de/10013156186
Cover Image
Non-Parametric Estimation of Conditional Densities : A New Method
Otneim, Håkon - 2016
Let X = (X1,...,Xp) be a stochastic vector having joint density function fX(x) with partitions X1 = (X1,...,Xk) and X2 = (Xk 1,...,Xp). A new method for estimating the conditional density function of X1 given X2 is presented. It is based on locally Gaussian approximations, but simplified in...
Persistent link: https://www.econbiz.de/10012977928
Cover Image
Long Memory in Stock Returns : An Analysis Using a Wavelet Based Semi-Parametric Estimator
Bhandari, Avishek - 2018
in stock return volatility using traditional time and spectral domain estimators of long memory. The definitive ubiquity … and existence of long memory in the volatility of stock returns is an established stylized fact. The presence of long … long memory in the Indian stock returns and returns volatility. We find the presence of long memory in the volatility of …
Persistent link: https://www.econbiz.de/10012920334
Cover Image
An overview of modified semiparametric memory estimation methods
Busch, Marie; Sibbertsen, Philipp - 2018 - This version: March 6, 2018
Several modified estimation methods of the memory parameter have been introduced in the past years. They aim to decrease the upward bias of the memory parameter in cases of low frequency contaminations or an additive noise component, especially in situations with a short-memory process being...
Persistent link: https://www.econbiz.de/10011813775
Cover Image
Extracting business cycles using semi-parametric time-varying spectra with applications to US macroeconomic time series
Koopman, Siem Jan; Wong, Soon Yip - 2006
A growing number of empirical studies provides evidence that dynamic properties of macroeconomic time series have been changing over time. Model-based procedures for the measurement of business cycles should therefore allow model parameters to adapt over time. In this paper the time dependencies...
Persistent link: https://www.econbiz.de/10011350381
Cover Image
An overview of modified semiparametric memory estimation methods
Busch, Marie; Sibbertsen, Philipp - In: Econometrics : open access journal 6 (2018) 1, pp. 1-21
Several modified estimation methods of the memory parameter have been introduced in the past years. They aim to decrease the upward bias of the memory parameter in cases of low frequency contaminations or an additive noise component, especially in situations with a short-memory process being...
Persistent link: https://www.econbiz.de/10011823283
Cover Image
Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer-Valued Ar(P) Models
Drost, Feike C.; Van den Akker, Ramon; Werker, Bas J. M. - 2013
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on...
Persistent link: https://www.econbiz.de/10014217553
Cover Image
Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models
Drost, Feike C.; Van den Akker, Ramon; Werker, Bas J. M. - 2008
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on...
Persistent link: https://www.econbiz.de/10014050438