Extracts credible intervals from dynamitefit object.
Usage
# S3 method for dynamitefit
confint(object, parm, level = 0.95, ...)Arguments
- object
[
dynamitefit]
The model fit object.- parm
Ignored.
- level
[
numeric(1)]
Credible interval width.- ...
Ignored.
Value
The rows of the resulting matrix will be named using the following
logic: {parameter}_{time}_{category}_{group} where parameter is the
name of the parameter, time is the time index of the parameter,
category specifies the level of the response the parameter
is related to if the response is categorical, and group determines which
group of observations the parameter is related to in the case of random
effects and loadings. Non-applicable fields in the this syntax are set
to NA.
See also
Model outputs
as.data.frame.dynamitefit(),
as.data.table.dynamitefit(),
as_draws_df.dynamitefit(),
coef.dynamitefit(),
dynamite(),
get_code(),
get_data(),
get_parameter_dims(),
get_parameter_names(),
get_parameter_types(),
ndraws.dynamitefit(),
nobs.dynamitefit()
Examples
data.table::setDTthreads(1) # For CRAN
confint(gaussian_example_fit, level = 0.9)
#> 5% 95%
#> alpha_y_1_NA_NA NA NA
#> alpha_y_2_NA_NA 0.007403695 0.102271300
#> alpha_y_3_NA_NA 0.026818291 0.170070435
#> alpha_y_4_NA_NA 0.106474401 0.233709265
#> alpha_y_5_NA_NA 0.202245962 0.329303567
#> alpha_y_6_NA_NA 0.244517471 0.374195388
#> alpha_y_7_NA_NA 0.264860517 0.390203385
#> alpha_y_8_NA_NA 0.364657824 0.481656025
#> alpha_y_9_NA_NA 0.390251045 0.519935516
#> alpha_y_10_NA_NA 0.350259409 0.493769444
#> alpha_y_11_NA_NA 0.339647931 0.479354240
#> alpha_y_12_NA_NA 0.379105151 0.517119896
#> alpha_y_13_NA_NA 0.429418537 0.539820413
#> alpha_y_14_NA_NA 0.449291373 0.565293593
#> alpha_y_15_NA_NA 0.428129253 0.559286081
#> alpha_y_16_NA_NA 0.405106725 0.539687935
#> alpha_y_17_NA_NA 0.406249375 0.527570810
#> alpha_y_18_NA_NA 0.397965134 0.521399476
#> alpha_y_19_NA_NA 0.367372795 0.494963990
#> alpha_y_20_NA_NA 0.326038745 0.447364663
#> alpha_y_21_NA_NA 0.264277527 0.401382307
#> alpha_y_22_NA_NA 0.154396289 0.291815841
#> alpha_y_23_NA_NA 0.006143314 0.125536454
#> alpha_y_24_NA_NA -0.054135556 0.054412793
#> alpha_y_25_NA_NA -0.032642637 0.079734051
#> alpha_y_26_NA_NA 0.003366138 0.114504501
#> alpha_y_27_NA_NA 0.004254258 0.127682953
#> alpha_y_28_NA_NA 0.036157275 0.163582552
#> alpha_y_29_NA_NA 0.164811555 0.295641981
#> alpha_y_30_NA_NA 0.648446080 0.812868415
#> beta_y_z_NA_NA_NA 1.948189211 1.986526732
#> delta_y_x_1_NA_NA NA NA
#> delta_y_x_2_NA_NA -0.206186161 -0.109286886
#> delta_y_x_3_NA_NA -0.960344923 -0.852211076
#> delta_y_x_4_NA_NA -0.921221572 -0.840961053
#> delta_y_x_5_NA_NA -0.951310983 -0.880725964
#> delta_y_x_6_NA_NA -1.095729609 -1.026302030
#> delta_y_x_7_NA_NA -1.177665339 -1.103289229
#> delta_y_x_8_NA_NA -1.032715155 -0.966347567
#> delta_y_x_9_NA_NA -0.944653473 -0.867048071
#> delta_y_x_10_NA_NA -1.047478264 -0.974612825
#> delta_y_x_11_NA_NA -1.227764706 -1.166779539
#> delta_y_x_12_NA_NA -1.405266345 -1.330408188
#> delta_y_x_13_NA_NA -1.485610106 -1.425804367
#> delta_y_x_14_NA_NA -1.487403795 -1.420771444
#> delta_y_x_15_NA_NA -1.444387469 -1.377682768
#> delta_y_x_16_NA_NA -1.445068583 -1.389108904
#> delta_y_x_17_NA_NA -1.457626809 -1.386735478
#> delta_y_x_18_NA_NA -1.400237607 -1.336903543
#> delta_y_x_19_NA_NA -1.379003301 -1.315181150
#> delta_y_x_20_NA_NA -1.389038803 -1.314712353
#> delta_y_x_21_NA_NA -1.306833190 -1.240175454
#> delta_y_x_22_NA_NA -1.252919941 -1.176769426
#> delta_y_x_23_NA_NA -1.278993986 -1.205772470
#> delta_y_x_24_NA_NA -1.244055184 -1.166417314
#> delta_y_x_25_NA_NA -1.111023748 -1.032825737
#> delta_y_x_26_NA_NA -0.936925885 -0.862959308
#> delta_y_x_27_NA_NA -0.776103894 -0.700284094
#> delta_y_x_28_NA_NA -0.678539976 -0.597379166
#> delta_y_x_29_NA_NA -0.682123045 -0.569101335
#> delta_y_x_30_NA_NA -0.264287731 -0.169723560
#> delta_y_y_lag1_1_NA_NA NA NA
#> delta_y_y_lag1_2_NA_NA 0.027708475 0.112279697
#> delta_y_y_lag1_3_NA_NA 0.124036033 0.205535682
#> delta_y_y_lag1_4_NA_NA 0.130764498 0.185517352
#> delta_y_y_lag1_5_NA_NA 0.136492033 0.184274517
#> delta_y_y_lag1_6_NA_NA 0.158736589 0.201304342
#> delta_y_y_lag1_7_NA_NA 0.188315647 0.231988190
#> delta_y_y_lag1_8_NA_NA 0.214798375 0.248758601
#> delta_y_y_lag1_9_NA_NA 0.259610197 0.300849347
#> delta_y_y_lag1_10_NA_NA 0.338752175 0.384461000
#> delta_y_y_lag1_11_NA_NA 0.438129961 0.479043146
#> delta_y_y_lag1_12_NA_NA 0.503718900 0.543924974
#> delta_y_y_lag1_13_NA_NA 0.513800912 0.544819902
#> delta_y_y_lag1_14_NA_NA 0.472410979 0.504393001
#> delta_y_y_lag1_15_NA_NA 0.418696779 0.451670605
#> delta_y_y_lag1_16_NA_NA 0.388352290 0.418164448
#> delta_y_y_lag1_17_NA_NA 0.377276206 0.412230701
#> delta_y_y_lag1_18_NA_NA 0.376151400 0.408728180
#> delta_y_y_lag1_19_NA_NA 0.367539514 0.397232588
#> delta_y_y_lag1_20_NA_NA 0.338018022 0.375021582
#> delta_y_y_lag1_21_NA_NA 0.306734768 0.344375855
#> delta_y_y_lag1_22_NA_NA 0.266554888 0.306323389
#> delta_y_y_lag1_23_NA_NA 0.234300050 0.269088275
#> delta_y_y_lag1_24_NA_NA 0.221356890 0.257105545
#> delta_y_y_lag1_25_NA_NA 0.215469673 0.255943805
#> delta_y_y_lag1_26_NA_NA 0.178322712 0.218263071
#> delta_y_y_lag1_27_NA_NA 0.110185573 0.157259300
#> delta_y_y_lag1_28_NA_NA 0.018021725 0.074707567
#> delta_y_y_lag1_29_NA_NA -0.072873647 -0.008145746
#> delta_y_y_lag1_30_NA_NA 0.009613330 0.099267763
#> tau_y_x_NA_NA_NA 0.257309584 0.507787183
#> tau_y_y_lag1_NA_NA_NA 0.076722283 0.138777375
#> tau_alpha_y_NA_NA_NA 0.138715827 0.292341726
#> sigma_nu_y_alpha_NA_NA_NA 0.079070615 0.112890854
#> sigma_y_NA_NA_NA 0.191890368 0.204777832
#> nu_y_alpha_NA_NA_1 -0.153441765 -0.033595205
#> nu_y_alpha_NA_NA_2 -0.114870358 0.001979568
#> nu_y_alpha_NA_NA_3 0.027001837 0.147718391
#> nu_y_alpha_NA_NA_4 -0.017882874 0.095613705
#> nu_y_alpha_NA_NA_5 -0.106008453 0.014380618
#> nu_y_alpha_NA_NA_6 0.055439424 0.185745872
#> nu_y_alpha_NA_NA_7 -0.023017193 0.100281578
#> nu_y_alpha_NA_NA_8 -0.142686495 -0.022266947
#> nu_y_alpha_NA_NA_9 -0.084264491 0.033376400
#> nu_y_alpha_NA_NA_10 -0.134529718 -0.018109105
#> nu_y_alpha_NA_NA_11 0.051982517 0.167357658
#> nu_y_alpha_NA_NA_12 -0.086175678 0.030890085
#> nu_y_alpha_NA_NA_13 -0.036082414 0.087035765
#> nu_y_alpha_NA_NA_14 -0.057670042 0.054336202
#> nu_y_alpha_NA_NA_15 -0.132213481 -0.014068792
#> nu_y_alpha_NA_NA_16 0.119076150 0.238364409
#> nu_y_alpha_NA_NA_17 0.005173991 0.116344265
#> nu_y_alpha_NA_NA_18 -0.291157831 -0.163215599
#> nu_y_alpha_NA_NA_19 -0.012703344 0.106147747
#> nu_y_alpha_NA_NA_20 -0.032483541 0.086243555
#> nu_y_alpha_NA_NA_21 -0.183771946 -0.053739117
#> nu_y_alpha_NA_NA_22 -0.070798438 0.047959732
#> nu_y_alpha_NA_NA_23 -0.188532118 -0.060967399
#> nu_y_alpha_NA_NA_24 -0.148277532 -0.033708367
#> nu_y_alpha_NA_NA_25 -0.100581578 0.005855686
#> nu_y_alpha_NA_NA_26 -0.186197499 -0.070342890
#> nu_y_alpha_NA_NA_27 0.024401632 0.133348063
#> nu_y_alpha_NA_NA_28 -0.098378355 0.017171792
#> nu_y_alpha_NA_NA_29 -0.146828123 -0.024331134
#> nu_y_alpha_NA_NA_30 0.041307799 0.171703260
#> nu_y_alpha_NA_NA_31 -0.090290989 0.042255943
#> nu_y_alpha_NA_NA_32 -0.105095753 0.021553250
#> nu_y_alpha_NA_NA_33 -0.005556545 0.106832600
#> nu_y_alpha_NA_NA_34 0.035048445 0.156329137
#> nu_y_alpha_NA_NA_35 -0.026070957 0.094503926
#> nu_y_alpha_NA_NA_36 0.035325901 0.168270253
#> nu_y_alpha_NA_NA_37 0.013239204 0.145541801
#> nu_y_alpha_NA_NA_38 -0.060052740 0.057836406
#> nu_y_alpha_NA_NA_39 -0.061488674 0.052916808
#> nu_y_alpha_NA_NA_40 -0.093290477 0.027073552
#> nu_y_alpha_NA_NA_41 -0.125930729 -0.012921516
#> nu_y_alpha_NA_NA_42 -0.035912809 0.089873419
#> nu_y_alpha_NA_NA_43 -0.169963190 -0.051560721
#> nu_y_alpha_NA_NA_44 0.152443044 0.272365234
#> nu_y_alpha_NA_NA_45 0.021529702 0.149746237
#> nu_y_alpha_NA_NA_46 -0.113245738 0.011313838
#> nu_y_alpha_NA_NA_47 -0.047594049 0.083274829
#> nu_y_alpha_NA_NA_48 -0.089941051 0.029704044
#> nu_y_alpha_NA_NA_49 -0.015592602 0.105131029
#> nu_y_alpha_NA_NA_50 -0.077733483 0.055182110