predict_glmmLasso: Predicts on newdata from glmmLasso objects
In retowuest/autoMrP: Improving MrP with Ensemble Learning

predict_glmmLasso

R Documentation

Predicts on newdata from glmmLasso objects

glmmLasso() predicts on newdata objects from a glmmLasso object.

predict_glmmLasso(
  census,
  m,
  L1.x,
  lasso.L2.x,
  L2.unit,
  L2.reg,
  type = "response"
)

`census`	Census data. A `data.frame` whose column names include `L1.x`, `L2.x`, `L2.unit`, if specified, `L2.reg` and `pcs`, and either `bin.proportion` or `bin.size`.
`m`	A `glmmLasso()` object.
`L1.x`	Individual-level covariates. A character vector containing the column names of the individual-level variables in `survey` and `census` used to predict outcome `y`. Note that geographic unit is specified in argument `L2.unit`.
`lasso.L2.x`	Lasso context-level covariates. A character vector containing the column names of the context-level variables in `survey` and `census` to be used by the lasso classifier. If `NULL` and `lasso` is set to `TRUE`, then lasso uses the variables specified in `L2.x`. Default is `NULL`.
`L2.unit`	Geographic unit. A character scalar containing the column name of the geographic unit in `survey` and `census` at which outcomes should be aggregated.
`L2.reg`	Geographic region. A character scalar containing the column name of the geographic region in `survey` and `census` by which geographic units are grouped (`L2.unit` must be nested within `L2.reg`). Default is `NULL`.