Nothing
R/computeStdErrorCumulativeHazard.R
In flexrsurv: Flexible Relative Survival Analysis
Defines functions
.computeStdErrorCumulativeHazard_GA0B0AB_bh
.computeStdErrorCumulativeHazard_GA0B0AB
.computeStdErrorCumulativeHazard_GA0B0AB<-function(allparam, var,
Y, X0, X, Z,
step, Nstep,
intTD=intTD_NC, intweightsfunc=intweights_CAV_SIM,
intTD_base=intTD_base_NC,
nT0basis,
Spline_t0=BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE), Intercept_t0=TRUE,
ialpha0, nX0,
ibeta0, nX,
ialpha, ibeta,
nTbasis,
Spline_t =BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE),
listZSplineBasis,
Intercept_t_NPH=rep(TRUE, nX),
debug=FALSE, ...){
# compute std error of a cumulative hazard (log rate) if the model
# rate = exp(f(t)%*%gamma + X0%*%alpha0 + X%*%beta0(t) + sum( alphai(zi)betai(t) ))
# using the delta method
# var(Cumhaz) = t(grad(Cumahaz)) var(param) grad(CumaHaz)
#
# code from gr_ll_flexrsurv_fromto_GA0B0AB or gr_ll_flexrsurv_GA0B0AB
#
#################################################################################################################
#################################################################################################################
# the coef of the first t-basis is constraint to 1 for nat-spline, and n-sum(other beta) if BS using expand() method
#################################################################################################################
#################################################################################################################
#################################################################################################################
# allparam ; vector of all coefs
# gamma0 = allparam[1:nY0basis]
# alpha0= allparam[ialpha0]
# beta0= matrix(allparam[ibeta0], ncol=nX, nrow=nTbasis)
# alpha= diag(allparam[ialpha])
# beta= expand(matrix(allparam[ibeta], ncol=nZ, nrow=nTbasis-1))
# beta does not contains coef for the first t-basis
#################################################################################################################
# Y : object of class Surv
# X0 : non-time dependante variable (may contain spline bases expended for non-loglinear terms)
# X : log lineair but time dependante variable
# Z : objesct of class DeSignMatrixLPHNLL of time dependent variables (spline basis expended)
# step : lag of subinterval for numerical integration fr each observation
# Nstep : number of lag for each observation
# intTD : function to perform numerical integration
# intweightfunc : function to compute weightsfor numerical integration
# Knots_t0=NULL,Intercept_t0=FALSE, degree_t0=3, Boundary.knots_t0 time spline parameters for baseline hazard
# Knots_t=NULL,Intercept_t=FALSE, degree_t0=, Boundary.knots_t time spline parameters for time-dependant effects (same basis for each TD variable)
# nT0basis : number of spline basis for NPHLIN effects
# nX0 : nb of PH variables dim(X0)=c(nobs, nX0)
# nX : nb of NPHLIN variables dim(X)=c(nobs, nX)
# nTbasis : number of time spline basis
# ... not used args
# the function do not check the concorcance between length of parameter vectors and the number of knots and the Z@signature
# returned value : the log liikelihood of the model
if (debug) cat("# computing gradient of the cumulative hazard: .computeStdErrorCumulativeHazard_GA0B0AB\n")
if(dim(Y)[2] == 2){
gradcumhaz <-gr_cumhaz_flexrsurv_GA0B0AB(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
} else {
gradcumhaz <-gr_cumhaz_flexrsurv_fromto_GA0B0AB(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
}
ret <- sqrt(apply(gradcumhaz * tcrossprod(gradcumhaz, var), 1, sum))
attr(ret, "gradient") <- gradcumhaz
return(ret)
}
.computeStdErrorCumulativeHazard_GA0B0AB_bh<-function(allparam, var,
Y, X0, X, Z,
step, Nstep,
intTD=intTD_NC, intweightsfunc=intweights_CAV_SIM,
intTD_base=intTD_base_NC,
nT0basis,
Spline_t0=BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE), Intercept_t0=TRUE,
ialpha0, nX0,
ibeta0, nX,
ialpha, ibeta,
nTbasis,
Spline_t =BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE),
listZSplineBasis,
Intercept_t_NPH=rep(TRUE, nX),
debug=FALSE, ...){
# compute std error of a cumulative hazard (log rate) if the model
# rate = f(t)%*%gamma exp( X0%*%alpha0 + X%*%beta0(t) + sum( alphai(zi)betai(t) ))
# using the delta method
# var(Cumhaz) = t(grad(Cumahaz)) var(param) grad(CumaHaz)
#
# code from gr_ll_flexrsurv_fromto_GA0B0AB_bh or gr_ll_flexrsurv_GA0B0AB_bh
#
#################################################################################################################
#################################################################################################################
# the coef of the first t-basis is constraint to 1 for nat-spline, and n-sum(other beta) if BS using expand() method
#################################################################################################################
#################################################################################################################
#################################################################################################################
# allparam ; vector of all coefs
# gamma0 = allparam[1:nY0basis]
# alpha0= allparam[ialpha0]
# beta0= matrix(allparam[ibeta0], ncol=nX, nrow=nTbasis)
# alpha= diag(allparam[ialpha])
# beta= expand(matrix(allparam[ibeta], ncol=nZ, nrow=nTbasis-1))
# beta does not contains coef for the first t-basis
#################################################################################################################
# Y : object of class Surv
# X0 : non-time dependante variable (may contain spline bases expended for non-loglinear terms)
# X : log lineair but time dependante variable
# Z : objesct of class DeSignMatrixLPHNLL of time dependent variables (spline basis expended)
# step : lag of subinterval for numerical integration fr each observation
# Nstep : number of lag for each observation
# intTD : function to perform numerical integration
# intweightfunc : function to compute weightsfor numerical integration
# Knots_t0=NULL,Intercept_t0=FALSE, degree_t0=3, Boundary.knots_t0 time spline parameters for baseline hazard
# Knots_t=NULL,Intercept_t=FALSE, degree_t0=, Boundary.knots_t time spline parameters for time-dependant effects (same basis for each TD variable)
# nT0basis : number of spline basis for NPHLIN effects
# nX0 : nb of PH variables dim(X0)=c(nobs, nX0)
# nX : nb of NPHLIN variables dim(X)=c(nobs, nX)
# nTbasis : number of time spline basis
# ... not used args
# the function do not check the concorcance between length of parameter vectors and the number of knots and the Z@signature
# returned value : the log liikelihood of the model
if (debug) cat("# computing gradient of the cumulative hazard: .computeStdErrorCumulativeHazard_GA0B0AB_bh\n")
if(dim(Y)[2] == 2){
gradcumhaz <-gr_cumhaz_flexrsurv_GA0B0AB_bh(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
} else {
gradcumhaz <-gr_cumhaz_flexrsurv_fromto_GA0B0AB_bh(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
}
ret <- sqrt(apply(gradcumhaz * tcrossprod(gradcumhaz, var), 1, sum))
attr(ret, "gradient") <- gradcumhaz
return(ret)
}
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flexrsurv documentation built on June 7, 2023, 5:09 p.m.
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Defines functions .computeStdErrorCumulativeHazard_GA0B0AB_bh .computeStdErrorCumulativeHazard_GA0B0AB
.computeStdErrorCumulativeHazard_GA0B0AB<-function(allparam, var,
Y, X0, X, Z,
step, Nstep,
intTD=intTD_NC, intweightsfunc=intweights_CAV_SIM,
intTD_base=intTD_base_NC,
nT0basis,
Spline_t0=BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE), Intercept_t0=TRUE,
ialpha0, nX0,
ibeta0, nX,
ialpha, ibeta,
nTbasis,
Spline_t =BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE),
listZSplineBasis,
Intercept_t_NPH=rep(TRUE, nX),
debug=FALSE, ...){
# compute std error of a cumulative hazard (log rate) if the model
# rate = exp(f(t)%*%gamma + X0%*%alpha0 + X%*%beta0(t) + sum( alphai(zi)betai(t) ))
# using the delta method
# var(Cumhaz) = t(grad(Cumahaz)) var(param) grad(CumaHaz)
#
# code from gr_ll_flexrsurv_fromto_GA0B0AB or gr_ll_flexrsurv_GA0B0AB
#
#################################################################################################################
#################################################################################################################
# the coef of the first t-basis is constraint to 1 for nat-spline, and n-sum(other beta) if BS using expand() method
#################################################################################################################
#################################################################################################################
#################################################################################################################
# allparam ; vector of all coefs
# gamma0 = allparam[1:nY0basis]
# alpha0= allparam[ialpha0]
# beta0= matrix(allparam[ibeta0], ncol=nX, nrow=nTbasis)
# alpha= diag(allparam[ialpha])
# beta= expand(matrix(allparam[ibeta], ncol=nZ, nrow=nTbasis-1))
# beta does not contains coef for the first t-basis
#################################################################################################################
# Y : object of class Surv
# X0 : non-time dependante variable (may contain spline bases expended for non-loglinear terms)
# X : log lineair but time dependante variable
# Z : objesct of class DeSignMatrixLPHNLL of time dependent variables (spline basis expended)
# step : lag of subinterval for numerical integration fr each observation
# Nstep : number of lag for each observation
# intTD : function to perform numerical integration
# intweightfunc : function to compute weightsfor numerical integration
# Knots_t0=NULL,Intercept_t0=FALSE, degree_t0=3, Boundary.knots_t0 time spline parameters for baseline hazard
# Knots_t=NULL,Intercept_t=FALSE, degree_t0=, Boundary.knots_t time spline parameters for time-dependant effects (same basis for each TD variable)
# nT0basis : number of spline basis for NPHLIN effects
# nX0 : nb of PH variables dim(X0)=c(nobs, nX0)
# nX : nb of NPHLIN variables dim(X)=c(nobs, nX)
# nTbasis : number of time spline basis
# ... not used args
# the function do not check the concorcance between length of parameter vectors and the number of knots and the Z@signature
# returned value : the log liikelihood of the model
if (debug) cat("# computing gradient of the cumulative hazard: .computeStdErrorCumulativeHazard_GA0B0AB\n")
if(dim(Y)[2] == 2){
gradcumhaz <-gr_cumhaz_flexrsurv_GA0B0AB(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
} else {
gradcumhaz <-gr_cumhaz_flexrsurv_fromto_GA0B0AB(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
}
ret <- sqrt(apply(gradcumhaz * tcrossprod(gradcumhaz, var), 1, sum))
attr(ret, "gradient") <- gradcumhaz
return(ret)
}
.computeStdErrorCumulativeHazard_GA0B0AB_bh<-function(allparam, var,
Y, X0, X, Z,
step, Nstep,
intTD=intTD_NC, intweightsfunc=intweights_CAV_SIM,
intTD_base=intTD_base_NC,
nT0basis,
Spline_t0=BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE), Intercept_t0=TRUE,
ialpha0, nX0,
ibeta0, nX,
ialpha, ibeta,
nTbasis,
Spline_t =BSplineBasis(knots=NULL, degree=3, keep.duplicates=TRUE),
listZSplineBasis,
Intercept_t_NPH=rep(TRUE, nX),
debug=FALSE, ...){
# compute std error of a cumulative hazard (log rate) if the model
# rate = f(t)%*%gamma exp( X0%*%alpha0 + X%*%beta0(t) + sum( alphai(zi)betai(t) ))
# using the delta method
# var(Cumhaz) = t(grad(Cumahaz)) var(param) grad(CumaHaz)
#
# code from gr_ll_flexrsurv_fromto_GA0B0AB_bh or gr_ll_flexrsurv_GA0B0AB_bh
#
#################################################################################################################
#################################################################################################################
# the coef of the first t-basis is constraint to 1 for nat-spline, and n-sum(other beta) if BS using expand() method
#################################################################################################################
#################################################################################################################
#################################################################################################################
# allparam ; vector of all coefs
# gamma0 = allparam[1:nY0basis]
# alpha0= allparam[ialpha0]
# beta0= matrix(allparam[ibeta0], ncol=nX, nrow=nTbasis)
# alpha= diag(allparam[ialpha])
# beta= expand(matrix(allparam[ibeta], ncol=nZ, nrow=nTbasis-1))
# beta does not contains coef for the first t-basis
#################################################################################################################
# Y : object of class Surv
# X0 : non-time dependante variable (may contain spline bases expended for non-loglinear terms)
# X : log lineair but time dependante variable
# Z : objesct of class DeSignMatrixLPHNLL of time dependent variables (spline basis expended)
# step : lag of subinterval for numerical integration fr each observation
# Nstep : number of lag for each observation
# intTD : function to perform numerical integration
# intweightfunc : function to compute weightsfor numerical integration
# Knots_t0=NULL,Intercept_t0=FALSE, degree_t0=3, Boundary.knots_t0 time spline parameters for baseline hazard
# Knots_t=NULL,Intercept_t=FALSE, degree_t0=, Boundary.knots_t time spline parameters for time-dependant effects (same basis for each TD variable)
# nT0basis : number of spline basis for NPHLIN effects
# nX0 : nb of PH variables dim(X0)=c(nobs, nX0)
# nX : nb of NPHLIN variables dim(X)=c(nobs, nX)
# nTbasis : number of time spline basis
# ... not used args
# the function do not check the concorcance between length of parameter vectors and the number of knots and the Z@signature
# returned value : the log liikelihood of the model
if (debug) cat("# computing gradient of the cumulative hazard: .computeStdErrorCumulativeHazard_GA0B0AB_bh\n")
if(dim(Y)[2] == 2){
gradcumhaz <-gr_cumhaz_flexrsurv_GA0B0AB_bh(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
} else {
gradcumhaz <-gr_cumhaz_flexrsurv_fromto_GA0B0AB_bh(allparam=allparam, var=var,
Y=Y, X0=X0, X=X, Z=Z,
step=step, Nstep=Nstep,
intTD=intTD, intweightsfunc=intweightsfunc,
intTD_base=intTD_base,
nT0basis=nT0basis,
Spline_t0=Spline_t0, Intercept_t0=Intercept_t0,
ialpha0=ialpha0, nX0=nX0,
ibeta0=ibeta0, nX=nX,
ialpha=ialpha, ibeta=ibeta,
nTbasis=nTbasis,
Spline_t = Spline_t,
Intercept_t_NPH=Intercept_t_NPH,
debug=debug)
}
ret <- sqrt(apply(gradcumhaz * tcrossprod(gradcumhaz, var), 1, sum))
attr(ret, "gradient") <- gradcumhaz
return(ret)
}
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