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): ⦗╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 50/4000 (1.2%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 51/4000 (1.3%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 52/4000 (1.3%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 203/16000 (1.3%)
#> Elapsed: 0s | ETA: 0s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 100/4000 (2.5%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 98/4000 (2.5%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 97/4000 (2.4%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 97/4000 (2.4%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 392/16000 (2.5%)
#> Elapsed: 1s | ETA: 40s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 200/4000 (5.0%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 455/4000 (11.4%)
#> Chain 3 (Warmup): ⦗━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 632/4000 (15.8%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 456/4000 (11.4%)
#> Total (Warmup): ⦗━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1743/16000 (10.9%)
#> Elapsed: 2s | ETA: 16s
#> Chain 1 (Warmup): ⦗━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 450/4000 (11.2%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 464/4000 (11.6%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 852/4000 (21.3%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 488/4000 (12.2%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2254/16000 (14.1%)
#> Elapsed: 3s | ETA: 18s
#> Chain 1 (Warmup): ⦗━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 750/4000 (18.8%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 770/4000 (19.2%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 861/4000 (21.5%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 773/4000 (19.3%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3154/16000 (19.7%)
#> Elapsed: 3s | ETA: 12s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1050/4000 (26.2%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 856/4000 (21.4%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1077/4000 (26.9%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1097/4000 (27.4%)
#> Total (Warmup): ⦗━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4080/16000 (25.5%)
#> Elapsed: 4s | ETA: 12s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1350/4000 (33.8%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 865/4000 (21.6%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1369/4000 (34.2%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1395/4000 (34.9%)
#> Total (Warmup): ⦗━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4979/16000 (31.1%)
#> Elapsed: 4s | ETA: 9s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━⦘ 1650/4000 (41.2%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1137/4000 (28.4%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1677/4000 (41.9%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━⦘ 1709/4000 (42.7%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━⦘ 6173/16000 (38.6%)
#> Elapsed: 5s | ETA: 8s
#> Chain 1 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1900/4000 (47.5%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1507/4000 (37.7%)
#> Chain 3 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1957/4000 (48.9%)
#> Chain 4 (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 1995/4000 (49.9%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━⦘ 7359/16000 (46.0%)
#> Elapsed: 5s | ETA: 6s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━⦘ 2150/4000 (53.8%)
#> Chain 2 (Warmup): ⦗━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━━━⦘ 1807/4000 (45.2%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━⦘ 2243/4000 (56.1%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2291/4000 (57.3%)
#> Total (Warmup): ⦗━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━⦘ 8491/16000 (53.1%)
#> Elapsed: 6s | ETA: 5s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2400/4000 (60.0%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━━━━⦘ 2046/4000 (51.1%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2484/4000 (62.1%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2551/4000 (63.8%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 9481/16000 (59.3%)
#> Elapsed: 6s | ETA: 4s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━⦘ 2650/4000 (66.2%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━━━━⦘ 2316/4000 (57.9%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2754/4000 (68.8%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━⦘ 2824/4000 (70.6%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━━━━━⦘ 10544/16000 (65.9%)
#> Elapsed: 7s | ETA: 4s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2900/4000 (72.5%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2585/4000 (64.6%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━━⦘ 3008/4000 (75.2%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3090/4000 (77.2%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 11583/16000 (72.4%)
#> Elapsed: 8s | ETA: 3s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━⦘ 3150/4000 (78.8%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 2855/4000 (71.4%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3251/4000 (81.3%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3353/4000 (83.8%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 12609/16000 (78.8%)
#> Elapsed: 8s | ETA: 2s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3400/4000 (85.0%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━━⦘ 3106/4000 (77.6%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3496/4000 (87.4%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━⦘ 3612/4000 (90.3%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━⦘ 13614/16000 (85.1%)
#> Elapsed: 9s | ETA: 2s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━⦘ 3650/4000 (91.2%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3372/4000 (84.3%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 3767/4000 (94.2%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺⦘ 3901/4000 (97.5%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 14690/16000 (91.8%)
#> Elapsed: 9s | ETA: 1s
#> Chain 1 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺⦘ 3950/4000 (98.8%)
#> Chain 2 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━⦘ 3711/4000 (92.8%)
#> Chain 3 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Chain 4 (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⦘ 4000/4000 (100.0%)
#> Total (Sampling): ⦗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺⦘ 15661/16000 (97.9%)
#> Elapsed: 10s | 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 (2) 0.809 0.003 0.215 5790.509 1.000
#> intrusion (3) -1.170 0.004 0.267 4618.932 1.000
#> intrusion (4) -3.527 0.006 0.395 4226.898 1.000
#> intrusion (5) -7.429 0.010 0.634 4127.272 1.001
#> dreams (2) -0.404 0.002 0.175 5866.050 1.000
#> dreams (3) -3.298 0.004 0.290 4500.263 1.000
#> ... (use `summary(fit)$main` to see full output)
#>
#> Pairwise interactions:
#> mean mcse sd n_eff n_eff_mixt Rhat
#> intrusion-dreams 0.349 0 0.031 4910.030 1.000
#> intrusion-flash 0.214 0 0.029 5223.346 1.001
#> dreams-flash 0.280 0 0.028 5526.727 1.001
#> Note: NA values are suppressed in the print table. They occur here when an
#> indicator was zero across all iterations, so mcse/n_eff/n_eff_mixt/Rhat are undefined;
#> `summary(fit)$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.
# }