Variable selection in additive models by non-negative garrote
نویسندگان
چکیده
منابع مشابه
Variable Selection in Additive Models by Nonnegative Garrote
We adapt Breiman’s (1995) nonnegative garrote method to perform variable selection in nonparametric additive models. The technique avoids methods of testing for which no reliable distributional theory is available. In addition it removes the need for a full search of all possible models, something which is computationally intensive, especially when the number of variables is moderate to high. T...
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Robust selection of variables in a linear regression model is investigated. Many variable selection methods are available, but very few methods are designed to avoid sensitivity to vertical outliers aswell as to leverage points. The nonnegative garrotemethod is a powerful variable selection method, developed originally for linear regression but recently successfully extended to more complex reg...
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Additive regression models have been shown to be useful in many situations. Numerical estimation of these models is usually done using the back-tting technique. This iterative numerical procedure converges very fast but has the disadvantage of a complicated`hat matrix.' This paper proposes an estimator with an explicit`hat matrix' which does not use backktting. The asymptotic normality of the e...
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ژورنال
عنوان ژورنال: Statistical Modelling
سال: 2011
ISSN: 1471-082X,1477-0342
DOI: 10.1177/1471082x1001100304