Rsmlx (version 2023.1.5)

buildAll: 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
)

Value

a new Monolix project with a new statistical model.

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.

Examples

if (FALSE) {
# 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)

}

# 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