ozone

This is the ozone data used in Breiman and Friedman (1985). This dataset contains 330 observations, 
and each observation is a daily measurement.

COSSO is the short term for Component Selection and
        Smoothing Operator. The new regularization method automatically
        selects important function components by a soft-thresholding
        penalty in the context of smoothing spline ANOVA models.  The
        details about the procedures are given in the paper by Lin and
        Zhang (2007).

Chen-Yen Lin

cosso

COSSO, adaptive COSSO, variable selection for nonparametric
        smoothing spline (quantile) regression models.

ozone function

<tabular>ll</tabular>{
ozone 	Ozone readingtemp 	Temperature (degree F)invHt 	Inversion base height (feet) press 	Pressure gradient (mm Hg)vis  	Visibility (miles)milPress 	500 millibar pressure height (m)hum 	Humidity (percent) invTemp 	Inversion base temperature (degrees F)wind 	Wind speed (mph) }

format

Breiman, L and Friedman, J. (1985), "Estimating Optimal Transformations for Multiple Regression
and Correlation", JASA, <b>80</b>, 580--598.

ozone: Ozone pollution data in Los Angels, 1976

Description

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