Fast bootstrap estimation using matrix multiplication — get_boot_ests

Replaces the wide-dataframe summarize_at + gather/spread approach with direct matrix multiplication. For each cell, computes weighted sums across all M bootstrap replicates simultaneously using BLAS routines, avoiding the creation of 10k-column intermediate dataframes.

Usage

get_boot_ests_matrix(
  ec_dat,
  boot_weights_df,
  ego_id_col,
  cell_vars,
  estimator_type
)

Arguments

ec_dat: ego X cell data from get_ec_reports()
boot_weights_df: dataframe with .ego.id column and boot_weight_1..M columns
ego_id_col: name of the ego id column in ec_dat and boot_weights_df
cell_vars: vector of column names defining cells (age, sex, time period, etc)
estimator_type: either 'ind' (individual visibility) or 'agg' (aggregate visibility)

Value

long-form data frame with one row per cell per bootstrap replicate