Abstract
Under i.i.d. random vectors (X, Y), (X 1, Y 1), (X 2, Y 2), … in the regression analysis one is interested in the value of the so called response variable Y (in
) depending on the value of the observation vector X (in
, with distribution μ).
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© 2013 Springer Fachmedien Wiesbaden
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Ferrario, P.G. (2013). Least Squares Estimation via Plug-In. In: Local Variance Estimation for Uncensored and Censored Observations. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-02314-0_2
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DOI: https://doi.org/10.1007/978-3-658-02314-0_2
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Publisher Name: Springer Vieweg, Wiesbaden
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Online ISBN: 978-3-658-02314-0
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