pls_predict: Predict from a fitted PLS-SEM model

In plssem: Complex Partial Least Squares Structural Equation Modeling

Predict from a fitted PLS-SEM model

Description

Predict from a fitted PLS-SEM model

Usage

pls_predict(object, ...)

## S4 method for signature 'PlsModel'
pls_predict(
  object,
  approach = c("earliest", "direct"),
  newdata = NULL,
  std.ord.exp = FALSE,
  benchmark = "R2",
  benchmark.vars = c("endog", "exog", "all"),
  ...
)

Arguments

object	A fitted PlsModel object.
...	Additional arguments passed to internal helpers.
approach	Prediction approach. If approach = "earliest" (default), then only indicators of exogenous benchmark.vars are used for prediction. If approach = "direct", then all indicators are used.
newdata	Optional new data matrix/data frame.
std.ord.exp	Logical; standardize ordinal expectation scores.
benchmark	Benchmark type(s). Either length 1 (recycled) or one entry per indicator (optionally named). Supported: "r2", "rmse", "mae", "q2_predict", "acc", "ord_mae".
benchmark.vars	What predictions should be benchmarked? If benchmark.vars = "endog" (default), preidction benchmarks are applied to indicators of endogenous benchmark.vars. If benchmark.vars = "exog", preidction benchmarks are applied to indicators of exogenous benchmark.vars. If benchmark.vars = "all", prediction benchmarks are applied to all of the indicators in the model.

Value

A PlsSemPredict object with matrices and benchmark results.

plssem documentation built on Sept. 26, 2026, 5:06 p.m.