Description Usage Arguments Details Value Author(s) Examples
Fits a set of semiparametric mixed models, with a common design matrix, by
repeated calls to gamm4
. Only a single smooth term is
permitted.
1 2 | semipar.mix.mp(Y, x, param = NULL, random, data.ran, k = 10, norder = 4,
pen.order = 2, knots = "quantile", store.gamm4 = FALSE)
|
Y |
n \times V response matrix. |
x |
a vector giving the predictor upon which each column of |
param |
a matrix or vector for the parametric terms in the model. |
random |
a formula, passed to |
data.ran |
a required data frame containing the factors used for random effects. |
k |
number of knots. |
norder |
order of B-splines: the default, |
pen.order |
order of the derivative penalty. |
knots |
knot placement for the B-spline bases. The default,
|
store.gamm4 |
logical: should the |
Unlike semipar.mp
, this function does not use large matrix
multiplications to avoid looping through model fits. Instead it performs a
separate call to gamm4
to fit a semiparametric mixed
model for each column of Y
.
coef |
matrix of the coefficients obtained from
|
bsplinecoef |
matrix of B-spline coefficients. |
pwdf |
vector of pointwise effective degrees of freedom. |
pwlsp |
vector of pointwise log smoothing parameters: grid values maximizing the restricted likelihood at each point. |
B |
matrix of basis function values. |
C |
the constraint matrix. |
Z |
transformation matrix to impose constraints. |
basis |
B-spline basis object, of the type created by the fda package; the coefficient estimates are with respect to this basis. |
Yin-Hsiu Chen enjoychen0701@gmail.com and Philip Reiss phil.reiss@nyumc.org
1 2 3 4 5 6 7 |
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