Pareto function — pareto • R2BEAT

pareto(strata,current_cvs,target_size,tolerance,cv_caps,t0,inactive_cv,
                   min_cv,eps_inact,bracket_fac,max_iter,max_same_iter,minnumstrat,
                   beat1cv_fun,verbose,plot,plot_dir,plot_prefix,save_pdf,show_targets,     
                   show_caps,plot_convergence)

Arguments

strata: Data frame with strata information
current_cvs: Data frame with initial CV targets per domain.
target_size: Desired total sample size.
tolerance: Allowed shortfall from target_size (scalar, >= 0).
cv_caps: Optional data frame with columns DOM, VAR, MAX_CV to cap CVs by domain/variable. VAR can be V#, CV#, or integer index.
t0: Initial scaling factor for CV targets.
inactive_cv: CV values >= inactive_cv are treated as inactive targets.
min_cv: Lower bound for active CV targets after scaling.
bracket_fac: Multiplicative step used to expand the bracketing interval.
max_iter: Maximum bisection iterations.
max_same_iter: Stop bracketing if n(t) repeats this many times (caps plateau).
minnumstrat: Minimum sample size per stratum passed to beat1cv_fun.
beat1cv_fun: Optional function to compute expected CVs (e.g., beat.1cv_new).
verbose: If TRUE, print progress messages.
plot: If TRUE, plot CVs by domain and allocations.
plot_dir: Output directory for plots.
plot_prefix: Filename prefix for plot outputs.
save_pdf: If TRUE, save plots to a PDF file.
show_targets: If TRUE, overlay initial target CVs on plots.
show_caps: If TRUE, overlay CV caps on plots (when provided).
plot_convergence: If TRUE, create convergence plot showing bracketing and bisection

Examples

out <- pareto(
  strata = strata,
  current_cvs = cv_equal,
  target_size = target_value,
  tolerance = 5,
  cv_caps = caps,
  beat1cv_fun = beat.1cv_new,
  max_iter = 50,
  max_same_iter = 20,
  plot = TRUE,
  plot_dir = "outputs",
  plot_prefix = "italy_domains",
  show_targets = TRUE,     
  show_caps = TRUE      
)
#> Error: object 'cv_equal' not found