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Generalised Joint Regression Modelling

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R/bcontSurvGunivMIXED_ExcessHazard_LeftTruncation.R

R/bcontSurvGunivMIXED_ExcessHazard_LeftTruncation.R
In GJRM: Generalised Joint Regression Modelling

Defines functions bcontSurvGunivMIXED_ExcessHazard_LeftTruncation

Documented in bcontSurvGunivMIXED_ExcessHazard_LeftTruncation 

bcontSurvGunivMIXED_ExcessHazard_LeftTruncation <- function(params, respvec, VC, ps, AT = FALSE){
  
  c1 <- VC$hrate
  c2 <- exp(-VC$d.lchrate)
  c3 <- exp(-VC$d.rchrate)  
  
  c2.td <- exp(-VC$d.lchrate.td)
  c3.td <- exp(-VC$d.rchrate.td) 
  
  # C.i = VC$indvU*(-VC$d.lchrate) + VC$indvR*(-VC$d.lchrate)
  # C.i.td = VC$indvUT*(-VC$d.chrate.td) + VC$indvRT*(-VC$d.lchrate.td)
  
  #################################################################################   
  
  
  monP <- monP1 <- monP2 <- k <- 0; V <- list()

  etad <- etas1 <- etas2 <- l.ln <- NULL

  params1 <- params[1:VC$X1.d2]
  params1[VC$mono.sm.pos] <- exp( params1[VC$mono.sm.pos] )

  eta1 <- VC$X1%*%params1
  Xd1P <- VC$Xd1%*%params1


  indN <- as.numeric(Xd1P < 0)

  #if(!is.null(VC$indexT)) print(table(indN))

  Xd1P <- ifelse(Xd1P < VC$min.dn, VC$min.dn, Xd1P )

  if( any(indN == TRUE) && !is.null(VC$indexT) ){

    monP22 <- matrix(0, length(params),length(params))

    for(i in 1:length(VC$pos.pb)){

      V[[i]] <- as.numeric(diff(params1[ VC$pos.pb[[i]] ]) < 0)
      monP22[ VC$pos.pb[[i]], VC$pos.pb[[i]] ] <- t(VC$D[[i]]*V[[i]])%*%VC$D[[i]]

    }


    k <- VC$my.env$k

    monP2 <- k*monP22
    monP  <- k/2*crossprod(params, monP22)%*%params
    monP1 <- k*(monP22%*%params)

    VC$my.env$k <- k*2


  }


  ##################

  der.par1 <- der2.par1 <- params1

  der.par1[-c( VC$mono.sm.pos )] <- 1
  der2.par1[-c( VC$mono.sm.pos )] <- 0

  ##################

  
  
  pd1  <- probmS(eta1, VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)

  p1       <- pd1$pr
  dS1eta1  <- pd1$dS
  d2S1eta1 <- pd1$d2S
  d3S1eta1 <- pd1$d3S
  der2eta1dery1b1 <- t(t(VC$Xd1)*der.par1)
  dereta1derb1    <- t(t(VC$X1)*der.par1)


  if( any(unique(VC$cens) == "I") ){

    eta2     <- VC$X2%*%params1
    pd2      <- probmS(eta2, VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
    p2       <- pd2$pr
    dS2eta2  <- pd2$dS
    d2S2eta2 <- pd2$d2S
    d3S2eta2 <- pd2$d3S
    dereta2derb1 <- t(t(VC$X2)*der.par1)

  }else{

    eta2     <- rep(0.1, length(eta1)) # just to get the code running, a bit inefficient but clear what is below
    pd2      <- probmS(eta2, VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
    p2       <- pd2$pr
    dS2eta2  <- pd2$dS
    d2S2eta2 <- pd2$d2S
    d3S2eta2 <- pd2$d3S
    dereta2derb1 <- t(t(VC$X2)*der.par1)


  }
  
  
  # THIRD PREDICTOR due to the LEFT-TRUNCATED observations
  if( any(unique(VC$cens) %in% c('UT', 'LT', 'RT', 'IT') ) ){
    
    eta3     <- VC$X3%*%params1
    pd3      <- probmS(eta3, VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
    p3       <- pd3$pr
    dS3eta3  <- pd3$dS
    d2S3eta3 <- pd3$d2S
    d3S3eta3 <- pd3$d3S
    dereta3derb1 <- t(t(VC$X3)*der.par1)
  
  } else {
    
    eta3     <- rep(0.1, length(eta1)) # just to get the code running
    pd3      <- probmS(eta3, VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
    p3       <- pd3$pr
    dS3eta3  <- pd3$dS
    d2S3eta3 <- pd3$d2S
    d3S3eta3 <- pd3$d3S
    dereta3derb1 <- t(t(VC$X3)*der.par1)
    
  }



  
  
  ####################################################################################################################
  
  l.par <- VC$weights*( 
    
    VC$indvU*log( c1*p1 - dS1eta1*Xd1P ) + 
      
      VC$indvR*log( p1 ) + 
      
      VC$indvL*log( 1 - p1*c2 ) + 
      
      VC$indvI*log( mm(p1*c2 - p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr) ) +
      
      VC$indvUT*log( c1*p3^-1*p1 - p3^-1*dS1eta1*Xd1P ) +
      
      VC$indvRT*log( p3^-1*p1 ) +
      
      VC$indvLT*log( mm( 1 - p3^-1*p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr) ) +
      
      VC$indvIT*log( mm(p3^-1*p1*c2.td - p3^-1*p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr) ) # +
    
    # C.i + C.i.td
    
  )   
  
  res   <- -sum(l.par)
  
  
  ########################################################################################################################
  
  dl.dbe1 <- -VC$weights*(   
    
    
    VC$indvU*( c((c1*p1 - dS1eta1*Xd1P)^-1)*( c(c1*dS1eta1)*dereta1derb1 - c(d2S1eta1*Xd1P)*dereta1derb1 - c(dS1eta1)*der2eta1dery1b1 ) ) +
      
      VC$indvR*c(p1^-1*dS1eta1)*dereta1derb1 +
      
      VC$indvL*-c( ( 1 - p1*c2 )^-1*dS1eta1*c2 )*dereta1derb1 + # minus here in front from L censoring
      
      VC$indvI*c( mm( p1*c2 - p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr ) )^-1*(c(dS1eta1*c2)*dereta1derb1 - c(dS2eta2*c3)*dereta2derb1) +
      
      VC$indvUT*( c((c1*p1 - dS1eta1*Xd1P)^-1)*( c(c1*dS1eta1)*dereta1derb1 - c(d2S1eta1*Xd1P)*dereta1derb1 - c(dS1eta1)*der2eta1dery1b1 ) - c(p3^-1*dS3eta3)*dereta3derb1 ) +
      
      VC$indvRT*( c(p1^-1*dS1eta1)*dereta1derb1 - c(p3^-1*dS3eta3)*dereta3derb1 ) +
      
      VC$indvLT*( -c( mm( p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr )^-1*dS1eta1*c2.td )*dereta1derb1 + c( mm( p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr )^-1*dS3eta3 - p3^-1*dS3eta3 )*dereta3derb1 ) +
      
      VC$indvIT*( c( mm( p1*c2.td - p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr ) )^-1*( c(dS1eta1*c2.td)*dereta1derb1 - c(dS2eta2*c3.td)*dereta2derb1 ) - c(p3^-1*dS3eta3)*dereta3derb1 )
    
    
  )
  
  G <- colSums(dl.dbe1)
  
  ########################################################################################################################################################################   
  
  
  H <-  -(   
    
    # UNCENSORED CONTRIBUTION
    crossprod(c(VC$weights*VC$indvU*( ( c1*p1 - dS1eta1*Xd1P )^-1*(c1*d2S1eta1) ))*dereta1derb1, dereta1derb1 ) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-1*(d3S1eta1*Xd1P)  ))*dereta1derb1, dereta1derb1 ) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-1*d2S1eta1 ))*dereta1derb1, der2eta1dery1b1 ) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-1*d2S1eta1 ))*der2eta1dery1b1, dereta1derb1 ) +
      
      
      
      diag( colSums( t( t(c(VC$weights*VC$indvU*( c1*p1 - dS1eta1*Xd1P )^-1*(c1*dS1eta1) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvU*-( c1*p1 - dS1eta1*Xd1P )^-1*(d2S1eta1*Xd1P) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvU*-( c1*p1 - dS1eta1*Xd1P )^-1*dS1eta1 )*VC$Xd1)*der2.par1 ) ) ) +
      
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-2*(c1*dS1eta1)^2 ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-2*(d2S1eta1*Xd1P)^2 ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-2*dS1eta1^2 ))*der2eta1dery1b1, der2eta1dery1b1) +
      
      
      crossprod(c(VC$weights*VC$indvU*(2*( c1*p1 - dS1eta1*Xd1P )^-2*( (c1*dS1eta1)*(d2S1eta1*Xd1P) ) ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvU*( ( c1*p1 - dS1eta1*Xd1P )^-2*(c1*dS1eta1^2) ))*dereta1derb1, der2eta1dery1b1) +
      
      crossprod(c(VC$weights*VC$indvU*( ( c1*p1 - dS1eta1*Xd1P )^-2*(c1*dS1eta1^2) ))*der2eta1dery1b1, dereta1derb1 ) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-2*( (d2S1eta1*Xd1P)*dS1eta1 ) ))*dereta1derb1, der2eta1dery1b1) +
      
      crossprod(c(VC$weights*VC$indvU*(-( c1*p1 - dS1eta1*Xd1P )^-2*( (d2S1eta1*Xd1P)*dS1eta1 ) ))*der2eta1dery1b1, dereta1derb1) +
      
      
      
      
      # RIGHT CENSORED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvR*(-p1^-2*dS1eta1^2+p1^-1*d2S1eta1))*dereta1derb1, dereta1derb1) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvR*p1^-1*dS1eta1)*VC$X1)*der2.par1 ) ) ) -
      
      
      
      # LEFT CENSORED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvL*(( 1 - p1*c2 )^-2*(dS1eta1*c2)^2 +
                                         ( 1 - p1*c2 )^-1*(d2S1eta1*c2) ))*dereta1derb1, dereta1derb1) -
      
      diag( colSums( t( t(c(VC$weights*VC$indvL*( 1 - p1*c2 )^-1*(dS1eta1*c2) )*VC$X1)*der2.par1 ) ) ) +
      
      
      
      
      # INTERVAL CENSORED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvI*(mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(d2S1eta1*c2) ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvI*(-mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(d2S2eta2*c3) ))*dereta2derb1, dereta2derb1) +
      
      
      diag( colSums( t( t(c(VC$weights*VC$indvI*mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(dS1eta1*c2) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvI*-mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(dS2eta2*c3) )*VC$X2)*der2.par1 ) ) ) +
      
      
      crossprod(c(VC$weights*VC$indvI*(-mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2)^2))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvI*(-mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS2eta2*c3)^2))*dereta2derb1, dereta2derb1) +
      
      
      crossprod(c(VC$weights*VC$indvI*(mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2)*(dS2eta2*c3) ))*dereta1derb1, dereta2derb1) +
      
      crossprod(c(VC$weights*VC$indvI*(mm(p1*c2-p2*c3, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2)*(dS2eta2*c3) ))*dereta2derb1, dereta1derb1) +
      
      
      
      # UNCENSORED LEFT-TRUNCATED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvUT*( ( c1*p1 - dS1eta1*Xd1P )^-1*(c1*d2S1eta1) ))*dereta1derb1, dereta1derb1 ) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-1*(d3S1eta1*Xd1P)  ))*dereta1derb1, dereta1derb1 ) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-1*d2S1eta1 ))*dereta1derb1, der2eta1dery1b1 ) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-1*d2S1eta1 ))*der2eta1dery1b1, dereta1derb1 ) +
      
      
      
      diag( colSums( t( t(c(VC$weights*VC$indvUT*( c1*p1 - dS1eta1*Xd1P )^-1*(c1*dS1eta1) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvUT*-( c1*p1 - dS1eta1*Xd1P )^-1*(d2S1eta1*Xd1P) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvUT*-( c1*p1 - dS1eta1*Xd1P )^-1*dS1eta1 )*VC$Xd1)*der2.par1 ) ) ) +
      
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-2*(c1*dS1eta1)^2 ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-2*(d2S1eta1*Xd1P)^2 ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-2*dS1eta1^2 ))*der2eta1dery1b1, der2eta1dery1b1) +
      
      
      crossprod(c(VC$weights*VC$indvUT*(2*( c1*p1 - dS1eta1*Xd1P )^-2*( (c1*dS1eta1)*(d2S1eta1*Xd1P) ) ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvUT*( ( c1*p1 - dS1eta1*Xd1P )^-2*(c1*dS1eta1^2) ))*dereta1derb1, der2eta1dery1b1) +
      
      crossprod(c(VC$weights*VC$indvUT*( ( c1*p1 - dS1eta1*Xd1P )^-2*(c1*dS1eta1^2) ))*der2eta1dery1b1, dereta1derb1 ) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-2*( (d2S1eta1*Xd1P)*dS1eta1 ) ))*dereta1derb1, der2eta1dery1b1) +
      
      crossprod(c(VC$weights*VC$indvUT*(-( c1*p1 - dS1eta1*Xd1P )^-2*( (d2S1eta1*Xd1P)*dS1eta1 ) ))*der2eta1dery1b1, dereta1derb1) +
      
      
      crossprod(c(VC$weights*VC$indvUT*(-p3^-1*d2S3eta3 ))*dereta3derb1, dereta3derb1 ) +
      
      diag( colSums( t( t(-c(VC$weights*VC$indvUT*p3^-1*dS3eta3 )*VC$X3)*der2.par1 ) ) ) +
      
      
      crossprod(c(VC$weights*VC$indvUT*( p3^-2*dS3eta3^2 ))*dereta3derb1, dereta3derb1 ) +
      
      
      
      # RIGHT CENSORED LEFT-TRUNCATED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvRT*(-p1^-2*dS1eta1^2 + p1^-1*d2S1eta1))*dereta1derb1, dereta1derb1) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvRT*p1^-1*dS1eta1)*VC$X1)*der2.par1 ) ) ) +
      
      crossprod(c(VC$weights*VC$indvRT*(p3^-2*dS3eta3^2 - p3^-1*d2S3eta3))*dereta3derb1, dereta3derb1) +
      
      diag( colSums( t( t(-c(VC$weights*VC$indvRT*p3^-1*dS3eta3)*VC$X3)*der2.par1 ) ) ) +
      
      
      
      # LEFT CENSORED LEFT-TRUNCATED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvLT*( -mm(p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2.td)^2 - mm(p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*d2S1eta1*c2.td ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvLT*( (p3^-2 - mm(p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2)*dS3eta3^2 - (p3^-1 - mm(p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1)*d2S3eta3 ))*dereta3derb1, dereta3derb1) +
      
      crossprod(c(VC$weights*VC$indvLT*( mm(p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*dS3eta3*dS1eta1*c2.td ))*dereta1derb1, dereta3derb1) +
      
      crossprod(c(VC$weights*VC$indvLT*( mm(p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*dS1eta1*dS3eta3*c2.td ))*dereta3derb1, dereta1derb1) +
      
      
      diag( colSums( t( t(-c(VC$weights*VC$indvLT*mm( p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr )^-1*(dS1eta1*c2.td) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(-c(VC$weights*VC$indvLT*( p3^-1 - mm( p3 - p1*c2.td, min.pr = VC$min.pr, max.pr = VC$max.pr )^-1 )*dS3eta3 )*VC$X3)*der2.par1 ) ) ) +
      
      
      
      # INTERVAL CENSORED LEFT-TRUNCATED CONTRIBUTION
      crossprod(c(VC$weights*VC$indvIT*(mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(d2S1eta1*c2.td) ))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvIT*(-mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(d2S2eta2*c3.td) ))*dereta2derb1, dereta2derb1) +
      
      
      diag( colSums( t( t(c(VC$weights*VC$indvIT*mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(dS1eta1*c2.td) )*VC$X1)*der2.par1 ) ) ) +
      
      diag( colSums( t( t(c(VC$weights*VC$indvIT*-mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-1*(dS2eta2*c3.td) )*VC$X2)*der2.par1 ) ) ) +
      
      
      crossprod(c(VC$weights*VC$indvIT*(-mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2.td)^2))*dereta1derb1, dereta1derb1) +
      
      crossprod(c(VC$weights*VC$indvIT*(-mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS2eta2*c3.td)^2))*dereta2derb1, dereta2derb1) +
      
      
      crossprod(c(VC$weights*VC$indvIT*(mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2.td)*(dS2eta2*c3.td) ))*dereta1derb1, dereta2derb1) +
      
      crossprod(c(VC$weights*VC$indvIT*(mm(p1*c2.td-p2*c3.td, min.pr = VC$min.pr, max.pr = VC$max.pr)^-2*(dS1eta1*c2.td)*(dS2eta2*c3.td) ))*dereta2derb1, dereta1derb1) +
      
      
      crossprod(c(VC$weights*VC$indvIT*( p3^-2*dS3eta3^2 - p3^-1*d2S3eta3 ))*dereta3derb1, dereta3derb1 ) +
      
      diag( colSums( t( t(-c(VC$weights*VC$indvIT*p3^-1*dS3eta3 )*VC$X3)*der2.par1 ) ) )
    
    
    
  )
  
  
  ############################################################################################################################################################################################
  
  
  
  if(VC$extra.regI == "pC") H <- regH(H, type = 1)
  
  S.h  <- ps$S.h + monP2                                # hess
  S.h1 <- 0.5*crossprod(params, ps$S.h)%*%params + monP # lik
  S.h2 <- S.h%*%params + monP1                          # grad   
  
  
  S.res <- res
  res   <- S.res + S.h1
  G     <- G + S.h2
  H     <- H + S.h  
  
  if(VC$extra.regI == "sED") H <- regH(H, type = 2)   
  
  
  list(value = res, gradient = G, hessian = H, S.h = S.h, S.h1 = S.h1, S.h2 = S.h2, indN = indN, V = V, 
       l = S.res, l.ln = l.ln, l.par = l.par, ps = ps, k = VC$my.env$k, monP2 = monP2, params1 = params1,
       eta1 = eta1, p1 = p1, p2 = p2, p3 = p3, 
       pdf1 = -dS1eta1, pdf2 = -dS2eta2, pdf3 = -dS3eta3,
       dl.dbe1 = NULL, dl.dbe2 = NULL, dl.dteta.st = NULL,
       hrate     = VC$hrate, 
       d.lchrate = VC$d.lchrate,
       d.rchrate = VC$d.rchrate,
       d.lchrate.td = VC$d.lchrate.td,
       d.rchrate.td = VC$d.rchrate.td)
  
  
  

  
  
}

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GJRM documentation built on July 9, 2023, 7:15 p.m.

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