looloss: Loss Function for Leave One Out Error

In KRLS: Kernel-Based Regularized Least Squares

Description

Internal function that computes Leave-On-Out (LOO) Error for KRLS given a fixed value for lambda (the parameter that governs the tradeoff between model fit and complexity in KRLS). This function is called internally by krls to find value of lambda that minimizes the LOO error. It would normally not be called by the user directly.

Usage

looloss(y = NULL, Eigenobject = NULL,
lambda = NULL,eigtrunc=NULL)

Arguments

y	n by 1 vector of outcomes.
Eigenobject	Object from call to eigen that contains spectral decomposition of the n by n Kernel matrix.
lambda	Positive scalar value for lamnbda parameter.
eigtrunc	Positive scalar value that determines truncation of eigenvalues for lamnda search window. See krls for details. Default is NULL which means no truncation.

Value

Scalar value for LOO error.

Author(s)

Jens Hainmueller (Stanford) and Chad Hazlett (MIT)

See Also

krls

KRLS documentation built on May 2, 2019, 5:51 a.m.