Search Results - subject:"nonparametric regression"

A simple test for the parametric form of the variance function in nonparametric regression

Dette, Holger; Hetzler, Benjamin - In: Annals of the Institute of Statistical Mathematics 61 (2009) 4, pp. 861-886

Persistent link: https://www.econbiz.de/10008467098

A review on empirical likelihood methods for regression

Chen, Song; Keilegom, Ingrid Van - In: TEST: An Official Journal of the Spanish Society of … 18 (2009) 3, pp. 415-447

Persistent link: https://www.econbiz.de/10008469413

Box-Jenkins ve Nonparametrik Regresyon Yöntemlerinin Etkinliklerinin Karsilastirilmasi: IMKB-100 Endeksine Yonelik Bir Uygulama

ERDOGAN, Namýk Kemal; UZGOREN, Nevin - In: Istanbul University Econometrics and Statistics e-Journal 10 (2009) 1, pp. 1-19

used for analysing the monovariate time series is nonparametric regression method which is based on a certain function … the efficiency of Box-Jenkins method and nonparametric regression method, which are used for analysis of monovariate time … this aim the comparisons performed as for various performance criteria revealed that the nonparametric regression method …

Persistent link: https://www.econbiz.de/10008464038

Nonparametric estimation of oligopsony power in first-price auction

Chung, Chanjin; Tostão, Emílio - In: Journal of agricultural economics 60 (2009) 2, pp. 318-333

Persistent link: https://www.econbiz.de/10003845661

Some recent developments in nonparametric finance

Cai, Zongwu; Hong, Yongmiao - In: Nonparametric econometric methods, (pp. 379-432). 2009

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric...

Persistent link: https://www.econbiz.de/10015382578

Higher order bias reduction of kernel density and density derivative estimation at boundary points

Bearse, Peter; Rilstone, Paul - In: Nonparametric econometric methods, (pp. 319-331). 2009

A new, direct method is developed for reducing, to an arbitrary order, the boundary bias of kernel density and density derivative estimators. The basic asymptotic properties of the estimators are derived. Simple examples are provided. A number of simulations are reported, which demonstrate the...

Persistent link: https://www.econbiz.de/10015382580

Nonparametric estimation of multivariate CDF with categorical and continuous data

Ju, Gaosheng; Li, Rui; Liang, Zhongwen - In: Nonparametric econometric methods, (pp. 291-318). 2009

In this paper we construct a nonparametric kernel estimator to estimate the joint multivariate cumulative distribution function (CDF) of mixed discrete and continuous variables. We use a data-driven cross-validation method to choose optimal smoothing parameters which asymptotically minimize the...

Persistent link: https://www.econbiz.de/10015382581

Nonparametric estimation of production risk and risk preference functions

Kumbhakar, Subal C.; Tsionas, Efthymios G. - In: Nonparametric econometric methods, (pp. 223-260). 2009

This paper deals with estimation of risk and the risk preference function when producers face uncertainties in production (usually labeled as production risk) and output price. These uncertainties are modeled in the context of production theory where the objective of the producers is to maximize...

Persistent link: https://www.econbiz.de/10015382583

Consistency of a least squares orthonormal series estimator for a regression function

Delecroix, Michel; Protopopescu, Camelia - 2000

This paper establishes the almost. sure consistency of least. squares regression series estimators, in the L2-norm and the sup-norm, under very large assumptions on the underlying model. Three examples are considered in order to illustrate the general results: trigonometric series, Legendre...

Persistent link: https://www.econbiz.de/10010310181

Minimax optimal designs for nonparametric regression - a further optimality property of the uniform distribution

Biedermann, Stefanie; Dette, Holger - 2000

In the common nonparametric regression model y(i) = g(ti) + a (ti) ei , i=1….,n with i.i.d - noise and nonrepeatable …

Persistent link: https://www.econbiz.de/10010316465