Abstract
A partially linear regression model of the form is defined by
where X i =(x i1 ,...,x ip ) Tand T i =(t i1 ,...,t id ) T are vectors of explanatory variables, (X i ,T i ) are either independent and identically distributed (i.i.d.) random design points or fixed design points. β = (β 1 ,…, β p ) T is a vector of unknown parameters, g is an unknown function from ℝ;d to ℝ1, and ε1, …, εn are independent random errors with mean zero and finite variances of (Math)\( \sigma_i^2 = E\varepsilon 2_i^2 \)
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© 2000 Springer-Verlag Berlin Heidelberg
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Härdle, W., Liang, H., Gao, J. (2000). Introduction. In: Partially Linear Models. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57700-0_1
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DOI: https://doi.org/10.1007/978-3-642-57700-0_1
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1300-5
Online ISBN: 978-3-642-57700-0
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