smeObject: Fitted sme Object
Description
An object returned by the sme function, inheriting from class
sme, representing a fitted smoothing-splines mixed-effects modelValue
- An
sme object must contain the following components. - calla list containing an image of the
sme call that produced the object. - coefficientsan n+1 by p matrix where n is the number of subjects and
p is the number of knots used in the spline basis. The first row of the matrix corresponds
to the fitted values of the mean curve at the knots, and the remaining n rows correspond
to the fitted values of the individual deviations from the mean curve at the knots.
- fitteda vector of model fitted values corresponding to the original observations.
- logLikthe log-likelihood of the fitted model.
- residualsa vector of model residuals.
- nobsthe number of observations.
- dataa data frame of the original data used to fit the model with variables
y,
tme and ind corresponding to observations, time points and subject identifiers
respectively. - dfa vector consisting of named components
mu and v corresponding to the
degrees of freedom of the mean and subject curves respectively. - smoothingParametersa vector of named components
mu and v corresponding to
the smoothing parameters for the mean and subject curves respectively. - parametersa list with named components
sigmaSquared and D corresponding to
the error variance and (unregularized) variance of the random-effects respectively. - iterationsthe number of iterations of the EM algorithm that ran before convergence (or the
limit was reached)
- infoa numeric code indicating diagnostic information from the EM algorithm with zero
indicating a successful run.
- In some instances, an
sme object may also contain the following components. - knotsa vector of the knots used in the spline basis when they do not coincide with the
unique design time points.