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]