Create Lasso summary posterior estimates

Create Lasso summary posterior estimates

Usage

lassoSummardf(fit, covarsVec, ...)

Arguments

fit

compiled rxode2 nlmir2 model fit

covarsVec

character vector of covariates that need to be added

...

other parameters passed to brm(): warmup = 1000, iter = 2000, chains = 4, cores = 4, control = list(adapt_delta = 0.99, max_treedepth = 15)

Value

Horse shoe Summary data frame of all covariates

Author

Vishal Sarsani, Christian Bartels

Examples

if (FALSE) {
one.cmt <- function() {
  ini({
    tka <- 0.45; label("Ka")
    tcl <- log(c(0, 2.7, 100)); label("Cl")
    tv <- 3.45; label("V")
    eta.ka ~ 0.6
    eta.cl ~ 0.3
    eta.v ~ 0.1
    add.sd <- 0.7
  })
  model({
    ka <- exp(tka + eta.ka)
    cl <- exp(tcl + eta.cl)
    v <- exp(tv + eta.v)
    linCmt() ~ add(add.sd)
  })
}

d <- nlmixr2data::theo_sd
fit <- nlmixr2(one.cmt, d, est = "saem", control = list(print = 0))
covarsVec <- c("WT")

# Horseshoe summary posterior estimates:

#lassoDf <- lassoSummardf(fit,covarsVec,cores=2)
#brms sometimes may throw a Error in sink(type = “output”)
#Issue Should be fixed by uninstalling and re-installing rstan
}