Print a fastsae object
Usage
# S3 method for class 'fastsae'
print(x, ...)Examples
m <- eblup_fh(y ~ x1 + x2 + x3, vardir = "vardir", data = mys, print_result = FALSE)
print(m)
#>
#> ── Fast Small Area Estimation (fastsae) ────────────────────────────────────────
#> Call:
#> eblup_fh(formula = y ~ x1 + x2 + x3, vardir = "vardir", data = mys,
#> print_result = FALSE)
#>
#> ✔ Convergence: Yes (in 6 iterations)
#> Model: Fay-Herriot (Area-level)
#> Method: REML
#> Random effect variance (sigma2_u): 2.608103
#>
#> Fixed Effects Coefficients:
#> beta std.error zvalue pvalue
#> (Intercept) 3.1077510 0.7697687 4.0372527 0.0001
#> x1 -0.0019323 0.0098886 -0.1954019 0.8451
#> x2 0.0555184 0.0614129 0.9040187 0.3660
#> x3 0.0335344 0.0580013 0.5781663 0.5632
#>
#> EBLUP Estimates (First 6 domains):
#> domain y eblup vardir random_effect mse rse
#> 1 1 8.359527 7.612738 0.6618838 2.94266461 0.5616180 9.844182
#> 2 2 7.599650 6.782316 0.8374691 2.54539588 0.6784873 12.144869
#> 3 3 5.514137 5.187060 0.8822257 0.96692722 0.7190378 16.347620
#> 4 4 3.869326 4.201545 0.6581716 -1.31646412 0.5619314 17.841554
#> 5 5 6.305063 6.323679 1.2788021 -0.03796677 0.9370273 15.307573
#> 6 6 3.926807 4.048590 0.3878004 -0.81904048 0.3548310 14.713194
#> ... and 36 more rows.
#>