buildAll: Automatic complete statistical model building

In MarcLavielle/Rsmlx: R Speaks 'Monolix'

Automatic complete statistical model building

Description

buildAll builds the complete statistical model by iteratively calling functions buildmlx and buildVar

Penalization criterion can be either a custom penalization of the form gamma*(number of parameters), AIC (gamma=2) or BIC (gamma=log(N)).

Usage

buildAll(
  project = NULL,
  final.project = NULL,
  model = "all",
  prior = NULL,
  weight = NULL,
  coef.w1 = 0.5,
  cv.min = 0.001,
  fError.min = 0.001,
  paramToUse = "all",
  covToTest = "all",
  covToTransform = "none",
  center.covariate = FALSE,
  criterion = "BICc",
  linearization = FALSE,
  ll = T,
  test = T,
  direction = NULL,
  steps = 1000,
  max.iter = 20,
  explor.iter = 2,
  seq.cov = FALSE,
  seq.corr = TRUE,
  seq.cov.iter = 0,
  p.max = 0.1,
  p.min = c(0.075, 0.05, 0.1),
  print = TRUE,
  nb.model = 1,
  fix.param1 = NULL,
  fix.param0 = NULL,
  remove = T,
  add = T,
  delta = c(30, 10, 5),
  omega.set = NULL,
  pop.set1 = NULL,
  pop.set2 = NULL
)

Arguments

project	a string: the initial Monolix project
final.project	a string: the final Monolix project (default adds "_buildAll" to the original project)
model	components of the model to optimize c("residualError", "covariate", "correlation"), (default="all")
prior	list of prior probabilities for each component of the model (default=NULL)
weight	list of penalty weights for each component of the model (default=NULL)
coef.w1	multiplicative weight coefficient used for the first iteration only (default=0.5)
cv.min	value of the coefficient of variation below which an individual parameter is considered fixed (default=0.001)
fError.min	minimum fraction of residual variance for combined error model (default = 1e-3)
paramToUse	list of parameters possibly function of covariates (default="all")
covToTest	components of the covariate model that can be modified (default="all")
covToTransform	list of (continuous) covariates to be log-transformed (default="none")
center.covariate	TRUE/FALSE center the covariates of the final model (default=FALSE)
criterion	penalization criterion to optimize c("AIC", "BIC", "BICc", gamma)
linearization	TRUE/FALSE whether the computation of the likelihood is based on a linearization of the model (default=FALSE, deprecated)
ll	TRUE/FALSE compute the observe likelihood and the criterion to optimize at each iteration
test	TRUE/FALSE perform additional statistical tests for building the model (default=TRUE)
direction	method for covariate search c("full", "both", "backward", "forward"), (default="full" or "both")
steps	maximum number of iteration for stepAIC (default=1000)
max.iter	maximum number of iterations (default=20)
explor.iter	number of iterations during the exploratory phase (default=2)
seq.cov	TRUE/FALSE whether the covariate model is built before the correlation model
seq.corr	TRUE/FALSE whether the correlation model is built iteratively (default=TRUE)
seq.cov.iter	number of iterations before building the correlation model (only when seq.cov=F, default=0)
p.max	maximum p-value used for removing non significant relationships between covariates and individual parameters (default=0.1)
p.min	minimum p-values used for testing the components of a new model (default=c(0.075, 0.05, 0.1))
print	TRUE/FALSE display the results (default=TRUE)
nb.model	number of models to display at each iteration (default=1)
fix.param1	parameters with variability that cannot be removed (default=NULL)
fix.param0	parameters without variability that cannot be added (default=NULL)
remove	try to remove random effects (default=T)
add	try to add random effects (default=T)
delta	maximum difference in criteria for testing a new model (default=c(30,10,5))
omega.set	settings to define how a variance varies during iterations of SAEM
pop.set1	Monolix settings 1
pop.set2	Monolix settings 2

Details

See https://monolix.lixoft.com/rsmlx/ for more details.

Value

a new Monolix project with a new statistical model.

Examples

## Not run: 
# Build the complete statistical model using the default settings
r1 <- buildAll(project="warfarinPK_project.mlxtran")

# Force parameter Tlag to be fixed (no variability) and parameter Cl to vary
r2 <- buildAll(project="warfarinPK_project.mlxtran", fix.param0="Tlag", fix.param1="Cl")

# Estimate the log-likelihood by linearization of the model (faster)
r3 <- buildAll(project="warfarinPK_project.mlxtran", linearization=T)


## End(Not run)

# See http://monolix.lixoft.com/rsmlx/buildmlx/ for detailed examples of use of buildmlx
# Download the demo examples here: http://monolix.lixoft.com/rsmlx/installation

MarcLavielle/Rsmlx documentation built on June 11, 2024, 8:22 a.m.