logLik.kspm {KSPM} | R Documentation |
Returns the Log Likelihood value of the kernel semi parametric model represented by obect
evaluated at the estimated coefficients.
## S3 method for class 'kspm'
logLik(object, ...)
object |
an object of class "kspm", usually, a result of a call to kspm. |
... |
additional optional argument (currently unused). |
The function returns the Log Likelihood computed as follow: logLik = -\frac{1}{2} RSS
where RSS
is the residual sum of squares.
logLik of kspm fit
Catherine Schramm, Aurelie Labbe, Celia Greenwood
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.
kspm, extractAIC.kspm, deviance.kspm
x <- 1:15
y <- 3*x + rnorm(15, 0, 2)
fit <- kspm(y, kernel = ~ Kernel(x, kernel.function = "linear"))
logLik(fit)