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Nonparametric estimation and testing of interaction in additive models
Sperlich, Stefan; Tjostheim, Dag; Yang, Lijian - 1998
We consider an additive model with second order interaction terms. It is shown how the components of this model can be estimated using marginal integration, and the asymptotic distribution of the estimators is derived. Moreover, two test statistics for testing the presence of interactions are...
Persistent link: https://www.econbiz.de/10009574875
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Regression and contrast estimated based on adaptive regressograms depending on qualitative explanatory variables
Bunke, Olaf; Castell, Ernestina - 1998
sample and asymptotic properties of the adaptive estimator. We also comment on stepwise selection procedures. The details of …
Persistent link: https://www.econbiz.de/10009577458
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Constructive asymptotic equivalence of density estimation and Gaussian white noise
Nussbaum, Michael; Klemelä, Jussi - 1998
A recipe is provided for producing, from a sequence of procedures in the Gaussian regression model, an asymptotically equivalent sequence in the density estimation model with i. i. d. observations. The recipe is, to put it roughly, to calculate square roots of normalised frequencies over certain...
Persistent link: https://www.econbiz.de/10009578013
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A nonparametric test of the non-convexity of regression
Diack, Cheikh A. T.; Thomas-Agnan, Christine - 1998
nonnormality. The behavior of the test under the local alternatives is studied. -- least squares estimator ; test of convexity ; B …
Persistent link: https://www.econbiz.de/10009578020
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Semiparametric additive indices for binary response and generalized additive models
Härdle, Wolfgang; Huet, Sylvie; Mammen, Enno; … - 1998
Models are studied where the response Y and covariates X, T are assumed to fulfill E(Y|X; T) = G{XT β + α + m1(T1) + … + md(Td)}. Here G is a known (link) function, β is an unknown parameter, and m1, …, md are unknown functions. In particular, we consider additive binary response models...
Persistent link: https://www.econbiz.de/10009578571
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Computer-assisted generalized partial linear models
Müller, Marlene - 1997
A particular semiparametric model of interest is the generalized partial linear model (GPLM) which allows a nonparametric modeling of the influence of the continuous covariables. The paper reviews different estimation procedures based on kernel methods and test procedures on the correct...
Persistent link: https://www.econbiz.de/10009657892
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Asymptotic normality of parametric part in partially linear models with measurement error in the nonparametric part
Liang, Hua - 1997
the T's are measured with additive error. We derive an estimator of β by modification local-likelihood method. The … resulting estimator of β is shown to be asymptotically normal.We consider the partially linear model relating a response Y to … predictors (X,T) with mean function XT β + g(T) when the T's are measured with additive error. We derive an estimator of β by …
Persistent link: https://www.econbiz.de/10009657894
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Asymptotic properties of the nonparametric part in partial linear heteroscedastic regression models
Liang, Hua; Härdle, Wolfgang; Werwatz, Axel - 1997
Persistent link: https://www.econbiz.de/10009659060
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Quantile regression estimates for a class of linear and partially linear errors-in-variables models
He, Xuming; Liang, Hua - 1997
We consider the problem of estimating quantile regression coefficients in errors-in-variables models. When the error variables for both the response and the manifest variables have a joint distribution that is spherically symmetric but otherwise unknown, the regression quantile estimates based...
Persistent link: https://www.econbiz.de/10009661014
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Bootstrap approximations in a partially linear regression model
Härdle, Wolfgang; Liang, Hua; Sommerfeld, Volker - 1997
Persistent link: https://www.econbiz.de/10009661015