Design matrix for the model needed in Gauss-Legendre quadrature
Builds the design matrix for the whole model when the sum-to-zero constraints are specified. The function is called inside model.cons
for Gauss-Legendre quadrature.
design.matrix( formula, data.spec, Z.smf, Z.tensor, Z.tint, list.smf, list.tensor, list.tint, list.rd )
formula |
formula object identifying the model |
data.spec |
data frame that represents the environment from which the covariate values and knots are to be calculated |
Z.smf |
List of matrices that represents the sum-to-zero constraint to apply for |
Z.tensor |
List of matrices that represents the sum-to-zero constraint to apply for |
Z.tint |
List of matrices that represents the sum-to-zero constraint to apply for |
list.smf |
List of all smf.smooth.spec objects contained in the model |
list.tensor |
List of all tensor.smooth.spec objects contained in the model |
list.tint |
List of all tint.smooth.spec objects contained in the model |
list.rd |
List of all rd.smooth.spec objects contained in the model |
design matrix for the model
library(survPen) # standard spline of time with 4 knots data <- data.frame(time=seq(0,5,length=100),event=1,t0=0) form <- ~ smf(time,knots=c(0,1,3,5)) t1 <- eval(substitute(time), data) t0 <- eval(substitute(t0), data) event <- eval(substitute(event), data) # Setting up the model model.c <- model.cons(form,lambda=0,data.spec=data,t1=t1,t1.name="time", t0=rep(0,100),t0.name="t0",event=event,event.name="event", expected=NULL,expected.name=NULL,type="overall",n.legendre=20, cl="survPen(form,data,t1=time,event=event)",beta.ini=NULL) # Retrieving the sum-to-zero constraint matrices and the list of knots Z.smf <- model.c$Z.smf ; list.smf <- model.c$list.smf # Calculating the design matrix design.M <- design.matrix(form,data.spec=data,Z.smf=Z.smf,list.smf=list.smf, Z.tensor=NULL,Z.tint=NULL,list.tensor=NULL,list.tint=NULL,list.rd=NULL)
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