Summarize Ecological Inference Estimates

`summary' method for the class `ei'.

Usage

# S3 method for ei
summary(object, ...)

Arguments

object

An ei object from the function ei.

...

A list of options to return in graphs. See values below.

References

Gary King (1997). A Solution to the Ecological Inference Problem. Princeton: Princeton University Press.

Author

Gary King <<email: king@harvard.edu>> and Molly Roberts <<email: molly.e.roberts@gmail.com>>

Examples

data(sample_ei)
formula <- t ~ x
dbuf <- ei(formula = formula, total = "n", data = sample_ei)
#> ℹ Running 2x2 ei
#> ℹ Maximizing likelihood for `erho` = 0.5.
#> ℹ Running 2x2 ei

#> ℹ Maximizing likelihood for `erho` = 3.
#> ℹ Running 2x2 ei

#> ℹ Maximizing likelihood for `erho` = 5.
#> ℹ Running 2x2 ei

#> ℹ Maximizing likelihood for `erho` = 0.1.
#> ℹ Running 2x2 ei

#> ✔ Running 2x2 ei [2ms]
#> 
#> ⠙ Beginning importance sampling.
#> ✔ Beginning importance sampling. [1.2s]
#> 
summary(dbuf)
#> 
#> ── Summary ─────────────────────────────────────────────────────────────────────
#> 
#> ── Erho ──
#> 
#> 0.1
#> 
#> 
#> ── Esigma ──
#> 
#> 0.5
#> 
#> 
#> ── Ebeta ──
#> 
#> 0.5
#> 
#> 
#> ── N ──
#> 
#> 75
#> 
#> 
#> ── Resamp ──
#> 
#> 5
#> 
#> 
#> ── Maximum likelihood results in scale of estimation (and se's) ──
#> 
#>         Bb0       Bw0       sigB       sigW        rho Zb0 Zw0
#>  -1.1605918 0.8264157 -2.1410777 -1.8073480 0.03161319   0   0
#>   0.1175759 0.1130699  0.2519238  0.1606003 0.09794052   0   0
#> 
#> 
#> ── Untruncated psi's ──
#> 
#>         BB        BW       SB        SW        RHO
#>  0.1924523 0.7283171 0.117315 0.1632397 0.03134792
#> 
#> 
#> ── Truncated psi's (ultimate scale) ──
#> 
#>         BB        BW       SB       SW        RHO
#>  0.2055313 0.7137829 0.105718 0.147298 0.09501627
#> 
#> 
#> ── Aggregate Bounds ──
#> 
#>            betab     betaw
#> lower 0.09549504 0.3979843
#> upper 0.60893461 0.8031228
#> 
#> 
#> ── Estimates of Aggregate Quantities of Interest ──
#> 
#>         mean          sd
#> Bb 0.2041410 0.010082548
#> Bw 0.7173938 0.007955811
#> 
#> 
#> ── Precision ──
#> 
#> 4
#>