log_llh: Log-likelihood computation
In FlexVarJM: Estimate Joint Models with Subject-Specific Variance

log_llh

R Documentation

Log-likelihood computation

Description

Log-likelihood computation

Usage

log_llh(
  param,
  nb.e.a,
  nb.priorMean.beta,
  nb.alpha,
  competing_risk,
  nb.alpha.CR,
  variability_hetero,
  S,
  Zq,
  sharedtype,
  sharedtype_CR,
  hazard_baseline,
  hazard_baseline_CR,
  ord.splines,
  Xtime,
  Utime,
  nb_pointsGK,
  Xs,
  Us,
  Xslope,
  Uslope,
  Xs.slope,
  Us.slope,
  indices_beta_slope,
  Time,
  st_calc,
  B,
  Bs,
  wk,
  Z,
  P,
  left_trunc,
  Z_CR,
  X_base,
  offset,
  U,
  y.new.prog,
  event1,
  event2,
  Ind,
  Xs.0,
  Us.0,
  Xs.slope.0,
  Us.slope.0,
  P.0,
  st.0,
  Bs.0,
  B.CR,
  Bs.CR,
  Bs.0.CR,
  nb.e.a.sigma = nb.e.a.sigma,
  nb.omega = nb.omega,
  Otime = Otime,
  Wtime = Wtime,
  Os = Os,
  Ws = Ws,
  O_base = O_base,
  W_base = W_base,
  correlated_re = correlated_re,
  Os.0 = Os.0,
  Ws.0 = Ws.0
)

Arguments

`param`	a vector : paramaters to be estimated
`nb.e.a`	integer : number of RE
`nb.priorMean.beta`	integer : number of fixed effects
`nb.alpha`	integer : number of covariates in survival model
`competing_risk`	boolean : allow competing risk or not, FALSE by default
`nb.alpha.CR`	integer : number of covariates in survival model for competing risks
`variability_hetero`	boolean : allow the heterogeneous variability or not
`S`	integer : the number of QMC points
`Zq`	vector : sobol points
`sharedtype`	vector : dependence structure for survival model : "RE" (random effects) or "CV" (current value) or "CVS" (current value and slope) or "S" (slope)
`sharedtype_CR`	vector : dependence structure for competing risk survival model : "RE" (random effects) or "CV" (current value) or "CVS" (current value and slope) or "S" (slope)
`hazard_baseline`	char : baseline hazard function : "Exponential" or "Weibull" or "Splines"
`hazard_baseline_CR`	char : baseline hazard function, competing risk : "Exponential" or "Weibull" or "Splines"
`ord.splines`	integer : the order of splines function for baseline hazard function
`Xtime`	matrix : fixed effects at event time
`Utime`	matrix : RE at event time
`nb_pointsGK`	integer : number of points for Gauss-Kronrod approximation, 7 or 15 (default)
`Xs`	matrix : fixed effects at Gauss-Kronrod times
`Us`	matrix : RE at Gauss-Kronrod times
`Xslope`	matrix : fixed effects of slope at event times
`Uslope`	matrix : RE of slope at event times
`Xs.slope`	matrix : fixed effects of slope at Gauss-Kronrod times
`Us.slope`	matrix : RE of slope at Gauss-Kronrod times
`indices_beta_slope`	vector : position of beta which will be used in the slope computation
`Time`	vector : observed event times
`st_calc`	matrix : Gauss-Kronrod times
`B`	matrix : splines for baseline hazard function of event 1
`Bs`	matrix : splines for baseline survival function of event 1
`wk`	vector : Gauss-Kronrod weights
`Z`	matrix : covariates for survival function of event 1
`P`	vector : Time/2
`left_trunc`	boolean : left truncation indicator
`Z_CR`	matrix : covariates for survival function of event 2
`X_base`	matrix : fixed effects for longitudinal submodel
`offset`	vector : number of lines per subjects
`U`	matrix : RE for longitudinal submodel
`y.new.prog`	vector : y measures for longitudinal submodel
`event1`	vector : event 1 indicator
`event2`	vector : event 2 indicator
`Ind`	integer : number of subjects
`Xs.0`	same for left truncation
`Us.0`	same for left truncation
`Xs.slope.0`	same for left truncation
`Us.slope.0`	same for left truncation
`P.0`	same for left truncation
`st.0`	same for left truncation
`Bs.0`	same for left truncation
`B.CR`	same for left truncation
`Bs.CR`	same for left truncation
`Bs.0.CR`	same for left truncation
`nb.e.a.sigma`	integer : number of RE for variability
`nb.omega`	integer : number of fixed effects for variability
`Otime`	matrix : fixed effects of variability at event time
`Wtime`	matrix : RE of variability at event time
`Os`	matrix : fixed effects of variability at Gauss-Kronrod times
`Ws`	matrix : random effects of variability at Gauss-Kronrod times
`O_base`	matrix : fixed effects for variability
`W_base`	matrix : fixed effects for variability
`correlated_re`	boolean : indicator to allow all the random effects to be correlated
`Os.0`	matrix : same for left truncation
`Ws.0`	matrix : same for left truncation