booami_sim: Example dataset for 'booami' (Gaussian, MAR)
In booami: Component-Wise Gradient Boosting after Multiple Imputation

booami_sim

R Documentation

Example dataset for 'booami' (Gaussian, MAR)

Description

A simulated dataset with predictors X1...X25 and a continuous outcome y. Missing values are generated under a MAR mechanism in the predictors (covariates) only; the outcome y is fully observed (no NAs). The object is a data.frame and carries attributes describing the data-generating process (true coefficients, informative indices, etc.).

Format

A data frame with 300 rows and 26 variables:

X1: numeric
X2: numeric
X3: numeric
X4: numeric
X5: numeric
X6: numeric
X7: numeric
X8: numeric
X9: numeric
X10: numeric
X11: numeric
X12: numeric
X13: numeric
X14: numeric
X15: numeric
X16: numeric
X17: numeric
X18: numeric
X19: numeric
X20: numeric
X21: numeric
X22: numeric
X23: numeric
X24: numeric
X25: numeric
y: numeric outcome (fully observed)

Details

Generated by simulate_booami_data with typical settings (see ?simulate_booami_data). The following attributes are attached to booami_sim:

"true_beta": numeric length-25 vector of true coefficients (non-zeros in positions 1-5).
"informative": integer vector 1:5.
"type": "gaussian".
"corr_structure": "all_ar1"; "rho": 0.3.
"intercept": 1; "noise_sd": 1 (Gaussian; NA otherwise).
"mar_scale": TRUE; "keep_mar_drivers": TRUE.

Examples

## \donttest{
utils::data(booami_sim)
dim(booami_sim)
mean(colSums(is.na(booami_sim)) > 0)  # fraction of columns with any NAs
sum(is.na(booami_sim$y))              # should be 0
head(attr(booami_sim, "true_beta"))
attr(booami_sim, "informative")
## }

booami documentation built on Feb. 19, 2026, 5:07 p.m.