logLik.kspm {KSPM}R Documentation

Log Likelihood of a kspm Object

Description

Returns the Log Likelihood value of the kernel semi parametric model represented by obect evaluated at the estimated coefficients.

Usage

## S3 method for class 'kspm'
logLik(object, ...)

Arguments

object

an object of class "kspm", usually, a result of a call to kspm.

...

additional optional argument (currently unused).

Details

The function returns the Log Likelihood computed as follow: logLik = -\frac{1}{2} RSS where RSS is the residual sum of squares.

Value

logLik of kspm fit

Author(s)

Catherine Schramm, Aurelie Labbe, Celia Greenwood

References

Liu, D., Lin, X., and Ghosh, D. (2007). Semiparametric regression of multidimensional genetic pathway data: least squares kernel machines and linear mixed models. Biometrics, 63(4), 1079:1088.

See Also

kspm, extractAIC.kspm, deviance.kspm

Examples

x <- 1:15
y <- 3*x + rnorm(15, 0, 2)
fit <- kspm(y, kernel = ~ Kernel(x, kernel.function = "linear"))
logLik(fit)


[Package KSPM version 0.2.1 Index]