smooth.cons: Design and penalty matrices of penalized splines in a...

In survPen: Multidimensional Penalized Splines for Survival and Net Survival Models

Design and penalty matrices of penalized splines in a smooth.spec object

Description

Builds the design and penalty matrices from the result of smooth.spec.

Usage

smooth.cons(
  term,
  knots,
  df,
  by = NULL,
  option,
  data.spec,
  same.rho = FALSE,
  name
)

Arguments

term	Vector of strings that generally comes from the value "term" of a smooth.spec object.
knots	List of numeric vectors that specifies the knots of the splines (including boundaries).
df	Degrees of freedom: numeric vector that indicates the number of knots desired for each covariate.
by	numeric or factor variable in order to define a varying coefficient smooth; default is NULL.
option	"smf", "tensor" or "tint".
data.spec	data frame that represents the environment from which the covariate values and knots are to be calculated; default is NULL.
same.rho	if there is a factor by variable, should the smoothing parameters be the same for all levels; default is FALSE.
name	simplified name of the smooth.spec call.

Value

List of objects with the following items:

X	Design matrix
pen	List of penalty matrices
term	Vector of strings giving the names of each covariate
knots	list of numeric vectors that specifies the knots for each covariate
dim	Number of covariates
all.df	Numeric vector giving the number of knots associated with each covariate
sum.df	Sum of all.df
Z.smf	List of matrices that represents the sum-to-zero constraint to apply for "smf" splines
Z.tensor	List of matrices that represents the sum-to-zero constraint to apply for "tensor" splines
Z.tint	List of matrices that represents the sum-to-zero constraint to apply for "tint" splines
lambda.name	name of the smoothing parameters

Examples

library(survPen)

# standard spline of time with 4 knots (so we get a design matrix with 3 columns 
# because of centering constraint)

data <- data.frame(time=seq(0,5,length=100))
smooth.c <- smooth.cons("time",knots=list(c(0,1,3,5)),df=4,option="smf",
data.spec=data,name="smf(time)")

survPen documentation built on Sept. 14, 2023, 1:06 a.m.