spsm_cubespline_design: Get design matrix for finding regression splines coefficients...
In gregorkb/semipadd2pop: Combine two data sets to fit semiparametric additive models
spsm_cubespline_design R Documentation
Get design matrix for finding regression splines coefficients under wiggliness penalization
Description
Get design matrix for finding regression splines coefficients under wiggliness penalization
Usage
spsm_cubespline_design(X, d, xi, W = NULL)
Arguments
X
a vector of values at which penalized cubic B-splines are to be evaluated
d
the number of B-spline functions in the basis. If negative, knots are evenly spaced.
xi
a parameter for penalizing towards smoothness
W
a vector of observation weights
Value
a list with the knots, the empirical centerings of the columns, and some matrices
gregorkb/semipadd2pop documentation built on Oct. 2, 2022, 1:37 p.m.
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| spsm_cubespline_design | R Documentation |
Get design matrix for finding regression splines coefficients under wiggliness penalization
Description
Get design matrix for finding regression splines coefficients under wiggliness penalization
Usage
spsm_cubespline_design(X, d, xi, W = NULL)
Arguments
X |
a vector of values at which penalized cubic B-splines are to be evaluated |
d |
the number of B-spline functions in the basis. If negative, knots are evenly spaced. |
xi |
a parameter for penalizing towards smoothness |
W |
a vector of observation weights |
Value
a list with the knots, the empirical centerings of the columns, and some matrices
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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