Returns fitted values for a funeigen
object.
1 2 |
object |
A |
type |
A character string, one of the following: |
... |
Other optional arguments which may be passed from other methods but ignored by this one. |
A funeigen
object represents a principal component analysis
of irregular longitudinal data, following the method used by Goldsmith et al. (2011).
A matrix or vector containing the appropriate fitted values. What is
returned depends on the type
parameter. functions
gives the fitted
values of the smooth latent x(t) functions at a grid of time points.
eigenfunctions
gives the estimated eigenfunctions at each time point.
loadings
gives the loading of each subject on each estimated eigenfunction.
mean
gives the mean value for the smooth latent x(t) functions.
centered
gives the centered x(t) functions (the estimated function
subtracting the mean function) . covariance
gives the estimated
covariance matrix of x(s) and x(t) on a grid of time points s and t.
noise.variance
gives the estimated measurement error variance on
the x(t) functions. midpoints
gives the time points for the grid, on
which functions
, mean
, centered
, and covariance
are defined; they are viewed as midpoints of bins of observation times (see
Goldsmith et al., 2011).
Goldsmith, J., Bobb, J., Crainiceanu, C. M., Caffo, B., and Reich, D. (2011). Penalized functional regression. Journal of Computational and Graphical Statistics, 20(4), 830-851. DOI: 10.1198/jcgs.2010.10007.
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