Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
نویسندگان
چکیده
منابع مشابه
A note on shrinkage sliced inverse regression
We employ Lasso shrinkage within the context of sufficient dimension reduction to obtain a shrinkage sliced inverse regression estimator, which provides easier interpretations and better prediction accuracy without assuming a parametric model. The shrinkage sliced inverse regression approach can be employed for both single-index and multiple-index models. Simulation studies suggest that the new...
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Sliced Inverse Regression (SIR) has been extensively used to reduce the dimension of the predictor space before performing regression. SIR is originally a model free method but it has been shown to actually correspond to the maximum likelihood of an inverse regression model with Gaussian errors. This intrinsic Gaussianity of standard SIR may explain its high sensitivity to outliers as observed ...
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In Li and Yin (2008, Biometrics 64, 124-131), a ridge SIR estimator is introduced as the solution of a minimization problem and computed thanks to an alternating least-squares algorithm. This methodology reveals good performance in practice. In this note, we focus on the theoretical properties of the estimator. It is shown that the minimization problem is degenerated in the sense that only two ...
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ژورنال
عنوان ژورنال: Atmospheric Chemistry and Physics
سال: 2009
ISSN: 1680-7324
DOI: 10.5194/acp-9-5321-2009