Returns posterior summaries and diagnostics for a fitted bgms model.
Usage
# S3 method for class 'bgms'
summary(object, ...)See also
bgm(), print.bgms(), coef.bgms()
Other posterior-methods:
coef.bgmCompare(),
coef.bgms(),
print.bgmCompare(),
print.bgms(),
summary.bgmCompare()
Examples
# \donttest{
fit = bgm(x = Wenchuan[, 1:3])
#> 2 rows with missing values excluded (n = 360 remaining).
#> To impute missing values instead, use na_action = "impute".
#> Chain 1 (Warmup): ⦗╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 50/4000 (1.2%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 51/4000 (1.3%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 52/4000 (1.3%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 52/4000 (1.3%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 205/16000 (1.3%)
#> Elapsed: 0s | ETA: 0s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 100/4000 (2.5%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 99/4000 (2.5%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 98/4000 (2.5%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 97/4000 (2.4%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 394/16000 (2.5%)
#> Elapsed: 1s | ETA: 40s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 200/4000 (5.0%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 456/4000 (11.4%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 674/4000 (16.9%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 456/4000 (11.4%)
#> Total (Warmup): ⦗━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1786/16000 (11.2%)
#> Elapsed: 2s | ETA: 16s
#> Chain 1 (Warmup): ⦗━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 450/4000 (11.2%)
#> Chain 2 (Warmup): ⦗━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 506/4000 (12.7%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 853/4000 (21.3%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 486/4000 (12.2%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2295/16000 (14.3%)
#> Elapsed: 3s | ETA: 18s
#> Chain 1 (Warmup): ⦗━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 750/4000 (18.8%)
#> Chain 2 (Warmup): ⦗━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 841/4000 (21.0%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 862/4000 (21.6%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 772/4000 (19.3%)
#> Total (Warmup): ⦗━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3225/16000 (20.2%)
#> Elapsed: 3s | ETA: 12s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1050/4000 (26.2%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 858/4000 (21.4%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1138/4000 (28.4%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1094/4000 (27.4%)
#> Total (Warmup): ⦗━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4140/16000 (25.9%)
#> Elapsed: 4s | ETA: 11s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1400/4000 (35.0%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 989/4000 (24.7%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1507/4000 (37.7%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1452/4000 (36.3%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 5348/16000 (33.4%)
#> Elapsed: 4s | ETA: 8s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1700/4000 (42.5%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1305/4000 (32.6%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1794/4000 (44.9%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1764/4000 (44.1%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━⦘ 6563/16000 (41.0%)
#> Elapsed: 5s | ETA: 7s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━⦘ 1950/4000 (48.8%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1677/4000 (41.9%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2092/4000 (52.3%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2054/4000 (51.3%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━⦘ 7773/16000 (48.6%)
#> Elapsed: 5s | ETA: 5s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2200/4000 (55.0%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━⦘ 1921/4000 (48.0%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2391/4000 (59.8%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━⦘ 2335/4000 (58.4%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━⦘ 8847/16000 (55.3%)
#> Elapsed: 6s | ETA: 5s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━⦘ 2450/4000 (61.3%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━⦘ 2212/4000 (55.3%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2700/4000 (67.5%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━⦘ 2609/4000 (65.2%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 9971/16000 (62.3%)
#> Elapsed: 7s | ETA: 4s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2700/4000 (67.5%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━⦘ 2518/4000 (62.9%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━⦘ 3011/4000 (75.3%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2864/4000 (71.6%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 11093/16000 (69.3%)
#> Elapsed: 7s | ETA: 3s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━⦘ 2950/4000 (73.8%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2795/4000 (69.9%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━⦘ 3309/4000 (82.7%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━⦘ 3131/4000 (78.3%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━⦘ 12185/16000 (76.2%)
#> Elapsed: 8s | ETA: 3s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3200/4000 (80.0%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━⦘ 3025/4000 (75.6%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3577/4000 (89.4%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━⦘ 3405/4000 (85.1%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━⦘ 13207/16000 (82.5%)
#> Elapsed: 8s | ETA: 2s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━⦘ 3450/4000 (86.2%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3296/4000 (82.4%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3858/4000 (96.5%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3654/4000 (91.3%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 14258/16000 (89.1%)
#> Elapsed: 9s | ETA: 1s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3700/4000 (92.5%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3667/4000 (91.7%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺⦘ 3918/4000 (98.0%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━⦘ 15285/16000 (95.5%)
#> Elapsed: 9s | ETA: 0s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 16000/16000 (100.0%)
#> Elapsed: 10s | ETA: 0s
summary(fit)
#> Posterior summaries from Bayesian estimation:
#>
#> Category thresholds:
#> mean mcse sd n_eff Rhat
#> intrusion (1) 0.807 0.003 0.219 6233.198 1.001
#> intrusion (2) -1.173 0.004 0.273 5020.987 1.002
#> intrusion (3) -3.525 0.006 0.403 4190.741 1.002
#> intrusion (4) -7.426 0.010 0.646 4129.567 1.001
#> dreams (1) -0.403 0.002 0.176 5757.133 1.001
#> dreams (2) -3.295 0.004 0.284 4295.270 1.001
#> ... (use `summary(fit)$main` to see full output)
#>
#> Pairwise interactions:
#> mean mcse sd n_eff n_eff_mixt Rhat
#> intrusion-dreams 0.349 0 0.031 4445.473 1.001
#> intrusion-flash 0.214 0 0.029 4885.911 1.001
#> dreams-flash 0.281 0 0.029 5501.458 1.000
#> Note: NA values are suppressed in the print table. They occur here when an
#> indicator was zero across all iterations, so mcse/n_eff/n_eff_mixt/Rhat are undefined;
#> `summary(fit)$pairwise` still contains the NA values.
#>
#> Inclusion probabilities:
#> mean mcse sd n0->0 n0->1 n1->0 n1->1 n_eff_mixt Rhat
#> intrusion-dreams 1 0 0 0 0 7999
#> intrusion-flash 1 0 0 0 0 7999
#> dreams-flash 1 0 0 0 0 7999
#> Note: NA values are suppressed in the print table. They occur when an indicator
#> was constant or had fewer than 5 transitions, so n_eff_mixt is unreliable;
#> `summary(fit)$indicator` still contains all computed values.
#>
#> Use `summary(fit)$<component>` to access full results.
#> Use `extract_log_odds(fit)` for log odds ratios.
#> See the `easybgm` package for other summary and plotting tools.
# }