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Adaptive weighting for flexible estimation in nonparametric regression models.

Nosedal-Sanchez, Alvaro - 2011

We propose a new method to find spatially adaptive smoothing splines. This new method breaks down the interval [0, 1] into p disjoint sub-intervals. Then we define p functional components in [0, 1], which have two importantfeatures. First, the purpose of each of these p components is to estimate...

Persistent link: https://www.econbiz.de/10009429662

Sample size determination for kernel regression estimation using sequential fixed-width confidence bands

Dharmasena, L. Sandamali; Zeephongsekul, P.; de Silva, … - 2008

We consider a random design model based on independent and identically distributed pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the...

Persistent link: https://www.econbiz.de/10009484098

Estimation for Generalized Linear Models When Covariates Are Subject-specific Parameters in a Mixed Model for Longitudinal Measurements

Li, Erning - 2005

approach.In order to estimate the distribution of random effects and to improve efficiency, we further propose a semiparametric … inferences under departures from this assumption and are competitive when the assumption holds. The semiparametric full …

Persistent link: https://www.econbiz.de/10009431291

Quasi-Monte Carlo for Highly Structured Generalised Response Models

Sloan, I. H.; Kuo, F. Y.; Dunsmuir, W. T.; Wand, M.; … - 2007

Highly structured generalised response models, such as generalised linear mixed models and generalised linear models for time series regression, have become an indispensable vehicle for data analysis and inference in many areas of application. However, their use in practice is hindered by...

Persistent link: https://www.econbiz.de/10009457431

Estimation of circadian parameters and investigation in cyanobacteria via semiparametric varying coefficient periodic models

Wang, Naisyin (contributor) - 2007

semiparametric varying coefficient periodic model which is suitable to studyperiodic patterns. This model has ample applications in …

Persistent link: https://www.econbiz.de/10009464826

Partly parametric generalized additive model

Zhang, Tianyang - 2010

In many scientific studies, the response variable bears a generalized nonlinear regression relationship with a certain covariate of interest, which may, however, be confounded by other covariates with unknown functional form. We propose a new class of models, the partly parametric generalized...

Persistent link: https://www.econbiz.de/10009466085

Rates of convergence for estimating regression coefficients in heteroskedastic discrete response models. (Author Abstract) Author Abstract

Chen, Songnian; Khan, Shakeeb - 2003

restriction, the semiparametric information bound is zero, even when the homoskedastic error term is parametrically specified …

Persistent link: https://www.econbiz.de/10009475499

Semiparametric Inference

He, Zhi - 2010

Semi-parametric and nonparametric modeling and inference have been widely studied duringthe last two decades. In this ….Firstly, we develop a semi-parametric additivity test for nonparametric multi-dimensionalmodel. The test statistic can test two or …

Persistent link: https://www.econbiz.de/10009477898

Policy Reform and Off-farm Labor Supply by Operators in the Delta Region: A

Mishra, Ashok K.; Paudel, Krishna P. - 2008

Off-farm employment has been an integral part of the emerging structure of production agriculture in the South. Government farm program payments, farm structure, and strong non-farm economy have important impact on labor allocation, farm and non-farm labor, decision of farm operators. The...

Persistent link: https://www.econbiz.de/10009443200

Generalized Volatility Model And Calculating VaR Using A New Semiparametric Model

Guo, Haiming - 2005

simulation, and extreme value theory. A new semiparametric model based on density ratio is developed in Chapter three. By … the VaR. We ran a monte carlo simulation to compare the semiparametric model and the traditional VaR models under many … different scenarios. In several cases, the semiparametric model performs quite satisfactorily. Furthermore, when applied to real …

Persistent link: https://www.econbiz.de/10009450634

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