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bbefkr (version 4.2)

Xvar: Simulated real-valued predictors in the semi-functional partial linear model

Description

Simulated real-valued predictors in the semi-functional partial linear model. It is a 50 by 2 matrix, where the column variables are generated from $U[0,1]$ and the true regression coefficients are (-1,2). Note that the estimation of the regression coefficient for these predictors depends crucially on the bandwidth parameter estimated in the functional Nadaraya-Watson estimator of the regression function

Usage

data(Xvar)

Arguments

Source

H. L. Shang (2013) Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density, Computational Statistics, in press.

References

H. L. Shang (2013) Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density, Computational Statistics, in press.

H. L. Shang (2013) Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density, Computational Statistics and Data Analysis, 67, 185-198.

Examples

Run this code
data(Xvar)
data(tau_semierr)
data(simresp_semi_normerr)

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