[PDF] Top 20 Nonlinear time series: semiparametric and nonparametric methods
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Nonlinear time series: semiparametric and nonparametric methods
... Empirical researchers have recently shown that nonparametric methods may be good alternatives to parametric methods in various cases. Its only prerequisite is that accurate data are used. Such an ... See full document
245
Assessing the adverse effects of interbank funds on bank efficiency through using semiparametric and nonparametric methods
... JEL Classification Codes: C14 Semiparametric and Nonparametric Methods, C67 Input–Output Models, G21 Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages Keywords:[r] ... See full document
43
Dimensionality reduction in nonparametric conditional density estimation with applications to nonlinear time series
... When one has a large amount of data, and it is possible to allocate a suitable validation set, it may be most bene…cial to terminate the algorithm based on the out-of-sample perfor- mance on the validation set. However, ... See full document
153
Nonparametric and semiparametric regression model selection
... in nonparametric and semiparametric ...fully nonparametric time series model for a given set of data, our research suggests using the computer-intensive semiparametric ... See full document
39
Comparison of methods for estimating the attributable risk in the context of survival analysis
... estimation methods have been proposed for survival data. Methods: Using simulations, we compared four methods for estimating AR defined in terms of survival functions: two nonparametric ... See full document
11
A nonparametric approach to detecting changes in variance in locally stationary time series
... In practice data sequences are often prone to outliers and/or heavy tail structures which the majority of approaches are intolerant to. Typically some pre-processing of the data is often performed in an attempt to ... See full document
37
Generalized Empirical Likelihood M Testing for Semiparametric Models with Time Series Data
... with time series ...a semiparametric time series regression model with endogenous covariates and a nonparametric generated ...estimated semiparametric electricity demand ... See full document
26
Effects of dating errors on nonparametric trend analyses of speleothem time series
... complex, nonlinear climate system (Lorenz, 1963) already make an inference (of trends) inexact and require us to report the uncertainty of a statistical analysis (Mudelsee, ...the methods they develop and ... See full document
12
Nonparametric Risk Bounds for Time-Series Forecasting
... Kernel-regularized methods, support-vector machines, relative-entropy based regulariza- tion, and kernel ridge regression among ...However, methods common to time-series such as AR models, ... See full document
40
Seasonal Decomposition for Geographical Time Series using Nonparametric Regression
... a time series, it often shows different systematic ...a time series, while a seasonal component logically explains effects that results from the changing seasons in a ...a time ... See full document
81
Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models
... 12 time series methods for short-term (day- ahead) spot price forecasting in auction-type electricity ...The methods considered in- clude standard autoregression (AR) models, their extensions ... See full document
23
Estimation of semiparametric econometric time series models with non linear or heteroscedastic disturbances
... Assuming that ut is stationary and independent of all the xt, Hannan (1963) proposed an estimate of 0 that has the same asymptotic efficiency as the best linear unbiased estimate, without employing a parametric model for ... See full document
224
Estimation of a Semiparametric Recursive Bivariate Probit Model with Nonparametric Mixing
... estimation methods are superior to conventional two-stage instrumental variable procedures ...The semiparametric version of Heckman ’ s model is an important extension since unde- tected nonlinearity can ... See full document
23
Estimation of a semiparametric recursive bivariate probit model with nonparametric mixing
... estimation methods are superior to conventional two-stage instrumental variable procedures ...The semiparametric version of Heckman ’ s model is an important extension since unde- tected nonlinearity can ... See full document
23
Estimation and model specification testing in nonparametric and semiparametric econometric models
... of series estimation to consistent testing for a parametric regression model; Shively, Kohn and Ansley (1994) consider testing for linearity in a semiparametric regres- sion model based on the stochastic ... See full document
45
The consistency for estimator of nonparametric regression model based on NOD errors
... the nonparametric estimator of g(t) based on NA samples, Hu [12] obtained the consistency and complete consistency for these esti- mations based on the linear time series, Baek and Liang [13] ... See full document
13
Analyzing the Kuznets Relationship using Nonparametric and Semiparametric Methods
... using nonparametric estimation based on a sample of cross-section country data, Mushinski (2001) showed that the quadratic parametric form of the relationship between Gini coefficient and real income per capita is ... See full document
34
Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series
... two semiparametric model averaging schemes for nonlinear dynamic time series regression models with a very large number of covariates including exogenous regressors and auto- regressive ...of ... See full document
31
Non-parametric smoothing and prediction for nonlinear circular time series
... the time series itself is somewhat erratic the selected smoothing parameters did not vary much — the ranges of concentration were ...most time points; the sum of errors (8) was ...the ... See full document
16
Nonparametric and semiparametric estimation and testing
... The problem Csorgo (1985) investigated was th at of testing for independence between ele ments in two i.i.d. series. He proposed to test for independence using a statistic of the form TVsupy |V>(u)|2, and he ... See full document
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