Auxiliary function for forecasting
Usage
# S3 method for fitted_dlm
forecast(
object,
t = 1,
plot = ifelse(requireNamespace("plotly", quietly = TRUE), "plotly",
ifelse(requireNamespace("ggplot2", quietly = TRUE), "ggplot2", "base")),
pred.cred = 0.95,
...
)Arguments
- object
fitted_dlm object: The fitted model to be use for predictions.
- t
numeric: Time window for prediction.
- plot
boolean or character: A flag indicating if a plot should be produced. Should be one of FALSE, TRUE, 'base', 'ggplot2' or 'plotly'.
- pred.cred
numeric: The credibility level for the C.I..
- ...
Extra variables necessary for prediction (covariates, etc.).
Value
A list containing:
data data.frame: A data frame contain the mean, variance and credibility intervals for the outcomes, including both the observed data and the predictions for future observations.
forecast data.frame: Same as data, but restricted to predictions for future observations.
outcomes list: A named list containing predictions for each outcome. Each element of this list is a list containing predictions (mean, variance and credibility intervals), the distribution of the linear predictor for the parameter of the observational model and the parameters of the predictive distribution (if available).
theta.mean matrix: A matrix with the values for the latent states at each time. Dimensions are n x t, where n is the number of latent states
theta.cov array: A 3D-array with the covariance of the latent states at each time. Dimensions are n x n x t, where n is the number of latent predictors.
lambda.mean matrix: A matrix with the values for the linear predictors at each time. Dimensions are k x t, where k is the number of linear predictors
lambda.cov array: A 3D-array with the covariance of the linear predictors at each time. Dimensions are k x k x t, where k is the number of linear predictors.
plot (if so chosen): A plotly or ggplot object.
A list containing:
data data.frame: A table with the model evaluated at each observed time, plus the forecasted period.
forecast data.frame: A table with the model evaluated at the forecasted period.
outcomes list: A list containing the parameters of the predictive distribution for each outcome at the forecasted period.
theta.mean matrix: The mean of the latent states at each forecasted time. Dimensions are n x t.forecast, where t.forecast is the size of the forecast windows and n is the number of latent states.
theta.cov array: A 3D-array containing the covariance matrix of the latent states at each forecasted time. Dimensions are n x n x t.forecast, where t.forecast is the size of the forecast windows and n is the number of latent states.
lambda.mean matrix: The mean of the linear predictor at each forecasted time. Dimensions are k x t.forecast, where t.forecast is the size of the forecast windows and k is the number of linear predictors.
lambda.cov array: A 3D-array containing the covariance matrix for the linear predictor at each forecasted time. Dimensions are k x k x t.forecast, where t.forecast is the size of the forecast windows and k is the number of linear predictors.
Details
If an a covariate is necessary for forecasting, it should be passed as a named argument. Its name must follow this structure: <block name>.Covariate<.index>. If there is only one covariate in the associated block the index is omitted. If an a pulse is necessary for forecasting, it should be passed as a named argument. Its name must follow this structure: <block name>.Pulse<.index>. If there is only one pulse in the associated block the index is omitted. The user may pass the observed values at the prediction windows (optional). See example. As an special case, if the model has an Multinomial outcome, the user may pass the N parameter instead of the observations. If an offset is necessary for forecasting, it should be passed with the same syntax as the observed data. See example.
See also
Other auxiliary functions for fitted_dlm objects:
coef.fitted_dlm(),
eval_dlm_norm_const(),
fit_model(),
kdglm(),
simulate.fitted_dlm(),
smoothing(),
update.fitted_dlm()
Examples
structure <-
polynomial_block(p = 1, order = 2, D = 0.95) +
harmonic_block(p = 1, period = 12, D = 0.975) +
noise_block(p = 1, R1 = 0.1) +
regression_block(
p = chickenPox$date >= as.Date("2013-09-1"),
# Vaccine was introduced in September of 2013
name = "Vaccine"
)
outcome <- Multinom(p = c("p.1", "p.2"), data = chickenPox[, c(2, 3, 5)])
fitted.data <- fit_model(structure * 2,
chickenPox = outcome
)
forecast(fitted.data, 24,
chickenPox = list(Total = rep(175, 24)), # Optional
Vaccine.1.Covariate = rep(TRUE, 24),
Vaccine.2.Covariate = rep(TRUE, 24)
)
#> Scale for y is already present.
#> Adding another scale for y, which will replace the existing scale.
#> $data
#> Time Serie Observation Prediction Variance C.I.lower
#> 1 1 chickenPox.< 5 year 218 213.58336 1970.0224 127
#> 2 2 chickenPox.< 5 year 215 213.08166 1826.3294 129
#> 3 3 chickenPox.< 5 year 256 248.92116 2230.5153 156
#> 4 4 chickenPox.< 5 year 271 262.87385 2058.2753 172
#> 5 5 chickenPox.< 5 year 348 333.57497 2708.1150 228
#> 6 6 chickenPox.< 5 year 333 320.15775 2177.4260 225
#> 7 7 chickenPox.< 5 year 397 385.62449 2918.9654 275
#> 8 8 chickenPox.< 5 year 459 478.25619 4110.7692 346
#> 9 9 chickenPox.< 5 year 811 769.97956 8030.5584 583
#> 10 10 chickenPox.< 5 year 932 889.36173 10562.4534 675
#> 11 11 chickenPox.< 5 year 730 694.17741 7446.8652 516
#> 12 12 chickenPox.< 5 year 460 453.79876 4141.3474 324
#> 13 13 chickenPox.< 5 year 214 227.84081 1349.9293 155
#> 14 14 chickenPox.< 5 year 133 148.90345 670.2821 98
#> 15 15 chickenPox.< 5 year 162 155.79359 724.2655 103
#> 16 16 chickenPox.< 5 year 227 196.43298 1054.3681 133
#> 17 17 chickenPox.< 5 year 231 212.43181 1125.4755 146
#> 18 18 chickenPox.< 5 year 179 196.43252 863.3400 138
#> 19 19 chickenPox.< 5 year 256 262.10029 1264.7064 191
#> 20 20 chickenPox.< 5 year 343 332.63869 1693.4840 249
#> 21 21 chickenPox.< 5 year 403 427.57466 2512.0559 325
#> 22 22 chickenPox.< 5 year 544 514.78942 3454.2190 394
#> 23 23 chickenPox.< 5 year 518 482.05868 3224.7552 366
#> 24 24 chickenPox.< 5 year 446 422.45053 2826.6894 315
#> 25 25 chickenPox.< 5 year 248 253.12430 1234.4500 183
#> 26 26 chickenPox.< 5 year 126 134.75607 434.3968 94
#> 27 27 chickenPox.< 5 year 113 143.53711 524.4366 99
#> 28 28 chickenPox.< 5 year 152 140.86369 490.6935 98
#> 29 29 chickenPox.< 5 year 157 154.50156 525.3190 109
#> 30 30 chickenPox.< 5 year 181 177.78759 571.2457 130
#> 31 31 chickenPox.< 5 year 222 226.91655 735.3450 172
#> 32 32 chickenPox.< 5 year 292 284.88427 946.1142 222
#> 33 33 chickenPox.< 5 year 521 489.48026 2425.7620 389
#> 34 34 chickenPox.< 5 year 587 574.50167 3318.6183 457
#> 35 35 chickenPox.< 5 year 495 456.24162 2311.7290 358
#> 36 36 chickenPox.< 5 year 363 323.04310 1382.0081 248
#> 37 37 chickenPox.< 5 year 157 185.44184 580.5863 137
#> 38 38 chickenPox.< 5 year 102 118.11201 294.5789 84
#> 39 39 chickenPox.< 5 year 132 136.94759 412.6463 97
#> 40 40 chickenPox.< 5 year 155 144.29627 449.6885 103
#> 41 41 chickenPox.< 5 year 217 211.47770 852.7351 154
#> 42 42 chickenPox.< 5 year 364 326.65769 1709.7904 245
#> 43 43 chickenPox.< 5 year 333 321.96834 1459.9463 246
#> 44 44 chickenPox.< 5 year 308 318.37241 1329.8531 245
#> 45 45 chickenPox.< 5 year 535 534.98008 2980.6070 423
#> 46 46 chickenPox.< 5 year 705 683.24551 4778.4721 542
#> 47 47 chickenPox.< 5 year 623 570.26250 3575.8874 449
#> 48 48 chickenPox.< 5 year 542 465.57851 2736.3861 360
#> 49 49 chickenPox.< 5 year 295 277.52804 1216.1768 208
#> 50 50 chickenPox.< 5 year 108 124.96477 321.2862 90
#> 51 51 chickenPox.< 5 year 85 108.54534 278.8636 76
#> 52 52 chickenPox.< 5 year 122 125.04087 368.6349 88
#> 53 53 chickenPox.< 5 year 145 159.28629 545.7949 114
#> 54 54 chickenPox.< 5 year 208 187.57580 657.4364 137
#> 55 55 chickenPox.< 5 year 191 202.02059 680.1540 150
#> 56 56 chickenPox.< 5 year 191 195.93931 597.7855 147
#> 57 57 chickenPox.< 5 year 289 291.02267 1213.6264 221
#> 58 58 chickenPox.< 5 year 374 358.47281 1846.4432 273
#> 59 59 chickenPox.< 5 year 305 285.28703 1277.6387 214
#> 60 60 chickenPox.< 5 year 297 262.95845 1206.1113 194
#> 61 61 chickenPox.< 5 year 156 156.87922 517.1706 112
#> 62 62 chickenPox.< 5 year 64 77.43775 159.3300 53
#> 63 63 chickenPox.< 5 year 97 98.33762 257.1332 67
#> 64 64 chickenPox.< 5 year 119 98.02634 255.3345 67
#> 65 65 chickenPox.< 5 year 96 101.10096 268.8404 70
#> 66 66 chickenPox.< 5 year 108 113.88600 318.7548 79
#> 67 67 chickenPox.< 5 year 127 141.19799 446.6542 100
#> 68 68 chickenPox.< 5 year 143 146.91046 459.8712 105
#> 69 69 chickenPox.< 5 year 191 184.75125 698.0615 133
#> 70 70 chickenPox.< 5 year 195 191.66894 770.6620 137
#> 71 71 chickenPox.< 5 year 153 146.94228 494.2250 104
#> 72 72 chickenPox.< 5 year 134 128.31627 409.6046 89
#> 73 73 chickenPox.< 5 year 79 92.57443 242.7741 63
#> 74 74 chickenPox.< 5 year 76 72.26792 162.2861 48
#> 75 75 chickenPox.< 5 year 88 81.43944 203.9909 54
#> 76 76 chickenPox.< 5 year 76 79.88421 195.5635 53
#> 77 77 chickenPox.< 5 year 84 91.69628 239.5374 62
#> 78 78 chickenPox.< 5 year 94 89.70525 217.3170 61
#> 79 79 chickenPox.< 5 year 126 124.00926 375.4526 87
#> 80 80 chickenPox.< 5 year 135 134.15747 432.9562 94
#> 81 81 chickenPox.< 5 year 152 148.87920 536.6530 104
#> 82 82 chickenPox.< 5 year 193 192.49156 903.0650 135
#> 83 83 chickenPox.< 5 year 151 146.47017 562.1278 101
#> 84 84 chickenPox.< 5 year 146 133.51518 487.5810 91
#> 85 85 chickenPox.< 5 year 105 108.33834 341.0566 73
#> 86 86 chickenPox.< 5 year 72 77.06402 187.9047 51
#> 87 87 chickenPox.< 5 year 90 94.09285 265.7415 63
#> 88 88 chickenPox.< 5 year 77 73.92722 169.1858 49
#> 89 89 chickenPox.< 5 year 90 86.80048 218.2579 59
#> 90 90 chickenPox.< 5 year 87 94.51491 246.3712 65
#> 91 91 chickenPox.< 5 year 110 106.02820 297.5535 73
#> 92 92 chickenPox.< 5 year 134 129.65846 436.4795 90
#> 93 93 chickenPox.< 5 year 132 133.79274 481.6768 92
#> 94 94 chickenPox.< 5 year 151 149.27467 616.5594 102
#> 95 95 chickenPox.< 5 year 138 127.81807 477.3924 86
#> 96 96 chickenPox.< 5 year 104 103.70684 331.9335 69
#> 97 97 chickenPox.< 5 year 67 91.03763 263.6324 60
#> 98 98 chickenPox.< 5 year 58 64.29270 140.5495 42
#> 99 99 chickenPox.< 5 year 94 85.36832 219.0392 57
#> 100 100 chickenPox.< 5 year 79 72.95833 160.3592 49
#> 101 101 chickenPox.< 5 year 93 93.88886 239.7493 64
#> 102 102 chickenPox.< 5 year 84 76.40348 162.0571 52
#> 103 103 chickenPox.< 5 year 96 100.03248 260.1230 69
#> 104 104 chickenPox.< 5 year 82 83.73816 194.3599 57
#> 105 105 chickenPox.< 5 year 80 88.56045 222.3970 60
#> 106 106 chickenPox.< 5 year 92 90.81995 242.2150 61
#> 107 107 chickenPox.< 5 year 77 80.35493 199.4477 54
#> 108 108 chickenPox.< 5 year 79 81.13588 202.1706 54
#> 109 109 chickenPox.< 5 year 73 72.87132 163.6432 49
#> 110 110 chickenPox.< 5 year 54 64.19351 127.1832 43
#> 111 111 chickenPox.< 5 year 133 101.96153 266.8406 71
#> 112 112 chickenPox.< 5 year 162 104.46116 276.8494 73
#> 113 113 chickenPox.< 5 year 102 86.42489 207.4812 59
#> 114 114 chickenPox.< 5 year 70 75.20901 169.4770 50
#> 115 115 chickenPox.< 5 year 79 80.53083 202.3640 54
#> 116 116 chickenPox.< 5 year 59 74.58019 193.4642 48
#> 117 117 chickenPox.< 5 year 49 67.78072 178.1302 43
#> 118 118 chickenPox.< 5 year 63 63.84081 171.8494 39
#> 119 119 chickenPox.< 5 year 63 66.32271 195.3912 40
#> 120 120 chickenPox.< 5 year 48 51.15106 132.2350 30
#> 121 1 chickenPox.5 to 9 years 64 65.59179 1970.0224 16
#> 122 2 chickenPox.5 to 9 years 43 53.88936 1826.3294 11
#> 123 3 chickenPox.5 to 9 years 60 61.31019 2230.5153 13
#> 124 4 chickenPox.5 to 9 years 47 55.70363 2058.2753 11
#> 125 5 chickenPox.5 to 9 years 66 69.43924 2708.1150 16
#> C.I.upper type
#> 1 299 Fit
#> 2 295 Fit
#> 3 339 Fit
#> 4 348 Fit
#> 5 430 Fit
#> 6 406 Fit
#> 7 484 Fit
#> 8 595 Fit
#> 9 931 Fit
#> 10 1075 Fit
#> 11 852 Fit
#> 12 574 Fit
#> 13 298 Fit
#> 14 199 Fit
#> 15 208 Fit
#> 16 259 Fit
#> 17 277 Fit
#> 18 252 Fit
#> 19 329 Fit
#> 20 409 Fit
#> 21 520 Fit
#> 22 623 Fit
#> 23 588 Fit
#> 24 522 Fit
#> 25 320 Fit
#> 26 175 Fit
#> 27 188 Fit
#> 28 184 Fit
#> 29 199 Fit
#> 30 223 Fit
#> 31 278 Fit
#> 32 342 Fit
#> 33 581 Fit
#> 34 681 Fit
#> 35 546 Fit
#> 36 393 Fit
#> 37 231 Fit
#> 38 151 Fit
#> 39 177 Fit
#> 40 186 Fit
#> 41 268 Fit
#> 42 406 Fit
#> 43 395 Fit
#> 44 387 Fit
#> 45 636 Fit
#> 46 812 Fit
#> 47 682 Fit
#> 48 564 Fit
#> 49 344 Fit
#> 50 160 Fit
#> 51 141 Fit
#> 52 163 Fit
#> 53 205 Fit
#> 54 237 Fit
#> 55 252 Fit
#> 56 243 Fit
#> 57 357 Fit
#> 58 440 Fit
#> 59 354 Fit
#> 60 330 Fit
#> 61 201 Fit
#> 62 102 Fit
#> 63 130 Fit
#> 64 130 Fit
#> 65 134 Fit
#> 66 149 Fit
#> 67 183 Fit
#> 68 189 Fit
#> 69 236 Fit
#> 70 246 Fit
#> 71 190 Fit
#> 72 168 Fit
#> 73 123 Fit
#> 74 98 Fit
#> 75 110 Fit
#> 76 108 Fit
#> 77 123 Fit
#> 78 119 Fit
#> 79 162 Fit
#> 80 175 Fit
#> 81 195 Fit
#> 82 252 Fit
#> 83 193 Fit
#> 84 177 Fit
#> 85 145 Fit
#> 86 105 Fit
#> 87 127 Fit
#> 88 100 Fit
#> 89 116 Fit
#> 90 126 Fit
#> 91 140 Fit
#> 92 171 Fit
#> 93 178 Fit
#> 94 199 Fit
#> 95 172 Fit
#> 96 140 Fit
#> 97 124 Fit
#> 98 88 Fit
#> 99 115 Fit
#> 100 98 Fit
#> 101 125 Fit
#> 102 102 Fit
#> 103 132 Fit
#> 104 112 Fit
#> 105 118 Fit
#> 106 122 Fit
#> 107 109 Fit
#> 108 110 Fit
#> 109 99 Fit
#> 110 87 Fit
#> 111 135 Fit
#> 112 138 Fit
#> 113 115 Fit
#> 114 101 Fit
#> 115 109 Fit
#> 116 103 Fit
#> 117 95 Fit
#> 118 91 Fit
#> 119 95 Fit
#> 120 75 Fit
#> 121 141 Fit
#> 122 122 Fit
#> 123 136 Fit
#> 124 126 Fit
#> 125 152 Fit
#> [ reached 'max' / getOption("max.print") -- omitted 307 rows ]
#>
#> $forecast
#> Time Serie Observation Variance Prediction C.I.lower
#> 1 121 chickenPox.< 5 year NA 135.5736 49.71787 28
#> 2 122 chickenPox.< 5 year NA 135.5736 48.69890 27
#> 3 123 chickenPox.< 5 year NA 135.5736 48.20482 26
#> 4 124 chickenPox.< 5 year NA 135.5736 48.26928 26
#> 5 125 chickenPox.< 5 year NA 135.5736 48.74705 26
#> 6 126 chickenPox.< 5 year NA 135.5736 49.30286 25
#> 7 127 chickenPox.< 5 year NA 135.5736 49.51656 25
#> 8 128 chickenPox.< 5 year NA 135.5736 49.07372 23
#> 9 129 chickenPox.< 5 year NA 135.5736 47.93041 22
#> 10 130 chickenPox.< 5 year NA 135.5736 46.30816 20
#> 11 131 chickenPox.< 5 year NA 135.5736 44.51784 18
#> 12 132 chickenPox.< 5 year NA 135.5736 42.80074 17
#> 13 133 chickenPox.< 5 year NA 135.5736 41.32312 15
#> 14 134 chickenPox.< 5 year NA 135.5736 40.24110 14
#> 15 135 chickenPox.< 5 year NA 135.5736 39.69342 14
#> 16 136 chickenPox.< 5 year NA 135.5736 39.72013 13
#> 17 137 chickenPox.< 5 year NA 135.5736 40.19498 13
#> 18 138 chickenPox.< 5 year NA 135.5736 40.82722 12
#> 19 139 chickenPox.< 5 year NA 135.5736 41.24545 12
#> 20 140 chickenPox.< 5 year NA 135.5736 41.14590 11
#> 21 141 chickenPox.< 5 year NA 135.5736 40.42889 10
#> 22 142 chickenPox.< 5 year NA 135.5736 39.21549 9
#> 23 143 chickenPox.< 5 year NA 135.5736 37.73478 8
#> 24 144 chickenPox.< 5 year NA 135.5736 36.21121 7
#> 25 121 chickenPox.5 to 9 years NA 135.5736 21.65348 8
#> 26 122 chickenPox.5 to 9 years NA 135.5736 18.60570 5
#> 27 123 chickenPox.5 to 9 years NA 135.5736 16.39643 4
#> 28 124 chickenPox.5 to 9 years NA 135.5736 15.30112 3
#> 29 125 chickenPox.5 to 9 years NA 135.5736 15.34896 3
#> 30 126 chickenPox.5 to 9 years NA 135.5736 16.46339 3
#> 31 127 chickenPox.5 to 9 years NA 135.5736 18.45239 4
#> 32 128 chickenPox.5 to 9 years NA 135.5736 20.88650 5
#> 33 129 chickenPox.5 to 9 years NA 135.5736 23.03546 6
#> 34 130 chickenPox.5 to 9 years NA 135.5736 24.07000 6
#> 35 131 chickenPox.5 to 9 years NA 135.5736 23.50624 5
#> 36 132 chickenPox.5 to 9 years NA 135.5736 21.53524 4
#> 37 133 chickenPox.5 to 9 years NA 135.5736 18.90456 3
#> 38 134 chickenPox.5 to 9 years NA 135.5736 16.45364 2
#> 39 135 chickenPox.5 to 9 years NA 135.5736 14.73308 1
#> 40 136 chickenPox.5 to 9 years NA 135.5736 13.95315 1
#> 41 137 chickenPox.5 to 9 years NA 135.5736 14.12701 1
#> 42 138 chickenPox.5 to 9 years NA 135.5736 15.18255 1
#> 43 139 chickenPox.5 to 9 years NA 135.5736 16.94978 1
#> 44 140 chickenPox.5 to 9 years NA 135.5736 19.06053 1
#> 45 141 chickenPox.5 to 9 years NA 135.5736 20.90129 2
#> 46 142 chickenPox.5 to 9 years NA 135.5736 21.78778 2
#> 47 143 chickenPox.5 to 9 years NA 135.5736 21.33572 1
#> 48 144 chickenPox.5 to 9 years NA 135.5736 19.72452 1
#> 49 121 chickenPox.15 to 49 years NA 135.5736 96.62864 72
#> 50 122 chickenPox.15 to 49 years NA 135.5736 100.69540 75
#> 51 123 chickenPox.15 to 49 years NA 135.5736 103.39875 77
#> 52 124 chickenPox.15 to 49 years NA 135.5736 104.42960 78
#> 53 125 chickenPox.15 to 49 years NA 135.5736 103.90399 76
#> 54 126 chickenPox.15 to 49 years NA 135.5736 102.23375 73
#> 55 127 chickenPox.15 to 49 years NA 135.5736 100.03105 70
#> 56 128 chickenPox.15 to 49 years NA 135.5736 98.03978 67
#> 57 129 chickenPox.15 to 49 years NA 135.5736 97.03413 65
#> 58 130 chickenPox.15 to 49 years NA 135.5736 97.62184 64
#> 59 131 chickenPox.15 to 49 years NA 135.5736 99.97592 66
#> 60 132 chickenPox.15 to 49 years NA 135.5736 103.66402 69
#> 61 133 chickenPox.15 to 49 years NA 135.5736 107.77232 73
#> 62 134 chickenPox.15 to 49 years NA 135.5736 111.30526 76
#> 63 135 chickenPox.15 to 49 years NA 135.5736 113.57350 78
#> 64 136 chickenPox.15 to 49 years NA 135.5736 114.32672 78
#> 65 137 chickenPox.15 to 49 years NA 135.5736 113.67801 76
#> 66 138 chickenPox.15 to 49 years NA 135.5736 111.99023 72
#> 67 139 chickenPox.15 to 49 years NA 135.5736 109.80477 68
#> 68 140 chickenPox.15 to 49 years NA 135.5736 107.79357 65
#> 69 141 chickenPox.15 to 49 years NA 135.5736 106.66982 62
#> 70 142 chickenPox.15 to 49 years NA 135.5736 106.99673 61
#> 71 143 chickenPox.15 to 49 years NA 135.5736 108.92951 62
#> 72 144 chickenPox.15 to 49 years NA 135.5736 112.06428 65
#> C.I.upper
#> 1 74
#> 2 73
#> 3 73
#> 4 74
#> 5 75
#> 6 77
#> 7 78
#> 8 79
#> 9 79
#> 10 78
#> 11 77
#> 12 76
#> 13 74
#> 14 74
#> 15 74
#> 16 75
#> 17 76
#> 18 79
#> 19 81
#> 20 82
#> 21 83
#> 22 83
#> 23 82
#> 24 80
#> 25 41
#> 26 37
#> 27 35
#> 28 34
#> 29 34
#> 30 37
#> 31 40
#> 32 45
#> 33 49
#> 34 51
#> 35 51
#> 36 49
#> 37 46
#> 38 42
#> 39 40
#> 40 40
#> 41 41
#> 42 44
#> 43 48
#> 44 53
#> 45 57
#> 46 60
#> 47 60
#> 48 58
#> 49 121
#> 50 125
#> 51 128
#> 52 129
#> 53 130
#> 54 129
#> 55 128
#> 56 127
#> 57 127
#> 58 129
#> 59 132
#> 60 135
#> 61 139
#> 62 142
#> 63 144
#> 64 145
#> 65 146
#> 66 146
#> 67 145
#> 68 145
#> 69 145
#> 70 146
#> 71 148
#> 72 150
#>
#> $outcomes
#> $outcomes$chickenPox
#> $outcomes$chickenPox$conj.param
#> alpha_1 alpha_2 alpha_3
#> 121 16.905993 7.363019 32.857462
#> 122 15.633856 5.973007 32.326348
#> 123 14.538583 4.945167 31.185083
#> 124 13.558861 4.298091 29.334317
#> 125 12.629936 3.976782 26.920622
#> 126 11.687022 3.902573 24.234050
#> 127 10.690872 3.983962 21.597200
#> 128 9.659035 4.111028 19.296883
#> 129 8.662543 4.163236 17.537140
#> 130 7.781518 4.044669 16.404155
#> 131 7.061989 3.728861 15.859457
#> 132 6.503896 3.272443 15.752533
#> 133 6.072196 2.777916 15.836524
#> 134 5.717802 2.337875 15.815208
#> 135 5.399034 2.003969 15.448081
#> 136 5.090677 1.788287 14.652534
#> 137 4.777907 1.679252 13.512707
#> 138 4.449060 1.654486 12.203897
#> 139 4.099407 1.684648 10.913553
#> 140 3.740901 1.732945 9.800373
#> 141 3.402080 1.758838 8.976237
#> 142 3.113179 1.729655 8.494092
#> 143 2.890148 1.634126 8.343031
#> 144 2.729502 1.486780 8.447100
#>
#> $outcomes$chickenPox$ft
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] -0.679083 -0.7432195 -0.7818002 -0.7919054 -0.7782452 -0.7518979
#> [2,] -1.549856 -1.7591244 -1.9299130 -2.0242632 -2.0246982 -1.9389059
#> [,7] [,8] [,9] [,10] [,11] [,12]
#> [1,] -0.7273409 -0.7185724 -0.7353596 -0.7806223 -0.8496504 -0.9313656
#> [2,] -1.7976785 -1.6466622 -1.5341261 -1.4980284 -1.5558459 -1.6998908
#> [,13] [,14] [,15] [,16] [,17] [,18] [,19]
#> [1,] -1.011290 -1.075427 -1.114008 -1.124113 -1.110453 -1.084105 -1.059548
#> [2,] -1.899371 -2.108639 -2.279428 -2.373778 -2.374213 -2.288421 -2.147194
#> [,20] [,21] [,22] [,23] [,24]
#> [1,] -1.050780 -1.067567 -1.112830 -1.181858 -1.263573
#> [2,] -1.996177 -1.883641 -1.847543 -1.905361 -2.049406
#>
#> $outcomes$chickenPox$Qt
#> , , 1
#>
#> [,1] [,2]
#> [1,] 0.111031031 0.002952275
#> [2,] 0.002952275 0.114880251
#>
#> , , 2
#>
#> [,1] [,2]
#> [1,] 0.123672883 0.003275323
#> [2,] 0.003275323 0.130104017
#>
#> , , 3
#>
#> [,1] [,2]
#> [1,] 0.136830380 0.003541592
#> [2,] 0.003541592 0.145910042
#>
#> , , 4
#>
#> [,1] [,2]
#> [1,] 0.149593768 0.003738337
#> [2,] 0.003738337 0.161078684
#>
#> , , 5
#>
#> [,1] [,2]
#> [1,] 0.161467867 0.003876132
#> [2,] 0.003876132 0.174921870
#>
#> , , 6
#>
#> [,1] [,2]
#> [1,] 0.172493799 0.003984471
#> [2,] 0.003984471 0.187492253
#>
#> , , 7
#>
#> [,1] [,2]
#> [1,] 0.183192092 0.004103871
#> [2,] 0.004103871 0.199515810
#>
#> , , 8
#>
#> [,1] [,2]
#> [1,] 0.194434525 0.004277022
#> [2,] 0.004277022 0.212174787
#>
#> , , 9
#>
#> [,1] [,2]
#> [1,] 0.207308809 0.004539212
#> [2,] 0.004539212 0.226871186
#>
#> , , 10
#>
#> [,1] [,2]
#> [1,] 0.222942264 0.004908079
#> [2,] 0.004908079 0.244987991
#>
#> , , 11
#>
#> [,1] [,2]
#> [1,] 0.242227680 0.005375258
#> [2,] 0.005375258 0.267588593
#>
#> , , 12
#>
#> [,1] [,2]
#> [1,] 0.265491167 0.005904707
#> [2,] 0.005904707 0.295057987
#>
#> , , 13
#>
#> [,1] [,2]
#> [1,] 0.292266282 0.006441238
#> [2,] 0.006441238 0.326834106
#>
#> , , 14
#>
#> [,1] [,2]
#> [1,] 0.321351876 0.006927658
#> [2,] 0.006927658 0.361440228
#>
#> , , 15
#>
#> [,1] [,2]
#> [1,] 0.351188944 0.007323712
#> [2,] 0.007323712 0.396907427
#>
#> , , 16
#>
#> [,1] [,2]
#> [1,] 0.380397001 0.007618777
#> [2,] 0.007618777 0.431442027
#>
#> , , 17
#>
#> [,1] [,2]
#> [1,] 0.408221257 0.007833981
#> [2,] 0.007833981 0.464034915
#>
#> , , 18
#>
#> [,1] [,2]
#> [1,] 0.434723899 0.008014972
#> [2,] 0.008014972 0.494756726
#>
#> , , 19
#>
#> [,1] [,2]
#> [1,] 0.460721555 0.008219696
#> [2,] 0.008219696 0.524685622
#>
#> , , 20
#>
#> [,1] [,2]
#> [1,] 0.487577799 0.008504881
#> [2,] 0.008504881 0.555595865
#>
#> , , 21
#>
#> [,1] [,2]
#> [1,] 0.51693605 0.00891269
#> [2,] 0.00891269 0.58956268
#>
#> , , 22
#>
#> [,1] [,2]
#> [1,] 0.55039436 0.00945864
#> [2,] 0.00945864 0.62854309
#>
#> , , 23
#>
#> [,1] [,2]
#> [1,] 0.58910514 0.01012381
#> [2,] 0.01012381 0.67392152
#>
#> , , 24
#>
#> [,1] [,2]
#> [1,] 0.63337341 0.01085602
#> [2,] 0.01085602 0.72606499
#>
#>
#> $outcomes$chickenPox$data
#> [,1] [,2] [,3]
#> [1,] 48 26 94
#> [2,] 48 26 94
#> [3,] 48 26 94
#> [4,] 48 26 94
#> [5,] 48 26 94
#> [6,] 48 26 94
#> [7,] 48 26 94
#> [8,] 48 26 94
#> [9,] 48 26 94
#> [10,] 48 26 94
#> [11,] 48 26 94
#> [12,] 48 26 94
#> [13,] 48 26 94
#> [14,] 48 26 94
#> [15,] 48 26 94
#> [16,] 48 26 94
#> [17,] 48 26 94
#> [18,] 48 26 94
#> [19,] 48 26 94
#> [20,] 48 26 94
#> [21,] 48 26 94
#> [22,] 48 26 94
#> [23,] 48 26 94
#> [24,] 48 26 94
#>
#> $outcomes$chickenPox$offset
#> [,1] [,2] [,3]
#> [1,] 1 1 1
#> [2,] 1 1 1
#> [3,] 1 1 1
#> [4,] 1 1 1
#> [5,] 1 1 1
#> [6,] 1 1 1
#> [7,] 1 1 1
#> [8,] 1 1 1
#> [9,] 1 1 1
#> [10,] 1 1 1
#> [11,] 1 1 1
#> [12,] 1 1 1
#> [13,] 1 1 1
#> [14,] 1 1 1
#> [15,] 1 1 1
#> [16,] 1 1 1
#> [17,] 1 1 1
#> [18,] 1 1 1
#> [19,] 1 1 1
#> [20,] 1 1 1
#> [21,] 1 1 1
#> [22,] 1 1 1
#> [23,] 1 1 1
#> [24,] 1 1 1
#>
#> $outcomes$chickenPox$pred
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 49.71787 48.6989 48.20482 48.26928 48.74705 49.30286 49.51656
#> [2,] 21.65348 18.6057 16.39643 15.30112 15.34896 16.46339 18.45239
#> [3,] 96.62864 100.6954 103.39875 104.42960 103.90399 102.23375 100.03105
#> [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] 49.07372 47.93041 46.30816 44.51784 42.80074 41.32312 40.24110
#> [2,] 20.88650 23.03546 24.07000 23.50624 21.53524 18.90456 16.45364
#> [3,] 98.03978 97.03413 97.62184 99.97592 103.66402 107.77232 111.30526
#> [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 39.69342 39.72013 40.19498 40.82722 41.24545 41.14590 40.42889
#> [2,] 14.73308 13.95315 14.12701 15.18255 16.94978 19.06053 20.90129
#> [3,] 113.57350 114.32672 113.67801 111.99023 109.80477 107.79357 106.66982
#> [,22] [,23] [,24]
#> [1,] 39.21549 37.73478 36.21121
#> [2,] 21.78778 21.33572 19.72452
#> [3,] 106.99673 108.92951 112.06428
#>
#> $outcomes$chickenPox$var.pred
#> , , 1
#>
#> [,1] [,2] [,3]
#> [1,] 135.57355 -24.81896 -110.75459
#> [2,] -24.81896 73.05560 -48.23663
#> [3,] -110.75459 -48.23663 158.99122
#>
#> , , 2
#>
#> [,1] [,2] [,3]
#> [1,] 139.71454 -21.78929 -117.92524
#> [2,] -21.78929 66.84333 -45.05404
#> [3,] -117.92524 -45.05404 162.97928
#>
#> , , 3
#>
#> [,1] [,2] [,3]
#> [1,] 145.4718 -19.91080 -125.56098
#> [2,] -19.9108 62.61923 -42.70843
#> [3,] -125.5610 -42.70843 168.26941
#>
#> , , 4
#>
#> [,1] [,2] [,3]
#> [1,] 153.61139 -19.63094 -133.98045
#> [2,] -19.63094 62.10207 -42.47113
#> [3,] -133.98045 -42.47113 176.45159
#>
#> , , 5
#>
#> [,1] [,2] [,3]
#> [1,] 164.37960 -21.15718 -143.22242
#> [2,] -21.15718 66.25356 -45.09638
#> [3,] -143.22242 -45.09638 188.31880
#>
#> , , 6
#>
#> [,1] [,2] [,3]
#> [1,] 177.33166 -24.59605 -152.73561
#> [2,] -24.59605 75.59808 -51.00203
#> [3,] -152.73561 -51.00203 203.73764
#>
#> , , 7
#>
#> [,1] [,2] [,3]
#> [1,] 191.39239 -29.80709 -161.58530
#> [2,] -29.80709 90.02198 -60.21489
#> [3,] -161.58530 -60.21489 221.80020
#>
#> , , 8
#>
#> [,1] [,2] [,3]
#> [1,] 205.03358 -36.00914 -169.0244
#> [2,] -36.00914 107.94844 -71.9393
#> [3,] -169.02444 -71.93930 240.9637
#>
#> , , 9
#>
#> [,1] [,2] [,3]
#> [1,] 216.66009 -41.56643 -175.09366
#> [2,] -41.56643 125.71681 -84.15038
#> [3,] -175.09366 -84.15038 259.24404
#>
#> , , 10
#>
#> [,1] [,2] [,3]
#> [1,] 225.18629 -44.54065 -180.64563
#> [2,] -44.54065 138.43644 -93.89579
#> [3,] -180.64563 -93.89579 274.54142
#>
#> , , 11
#>
#> [,1] [,2] [,3]
#> [1,] 230.34786 -43.84935 -186.49850
#> [2,] -43.84935 142.32401 -98.47466
#> [3,] -186.49850 -98.47466 284.97316
#>
#> , , 12
#>
#> [,1] [,2] [,3]
#> [1,] 232.68624 -40.02383 -192.66241
#> [2,] -40.02383 136.96216 -96.93832
#> [3,] -192.66241 -96.93832 289.60073
#>
#> , , 13
#>
#> [,1] [,2] [,3]
#> [1,] 233.73598 -34.88147 -198.85451
#> [2,] -34.88147 125.85370 -90.97223
#> [3,] -198.85451 -90.97223 289.82674
#>
#> , , 14
#>
#> [,1] [,2] [,3]
#> [1,] 236.08564 -30.40468 -205.68096
#> [2,] -30.40468 114.50279 -84.09812
#> [3,] -205.68096 -84.09812 289.77907
#>
#> , , 15
#>
#> [,1] [,2] [,3]
#> [1,] 242.57423 -27.85411 -214.72012
#> [2,] -27.85411 107.55218 -79.69807
#> [3,] -214.72012 -79.69807 294.41818
#>
#> , , 16
#>
#> [,1] [,2] [,3]
#> [1,] 255.12392 -27.75012 -227.37380
#> [2,] -27.75012 107.62351 -79.87338
#> [3,] -227.37380 -79.87338 307.24718
#>
#> , , 17
#>
#> [,1] [,2] [,3]
#> [1,] 274.09621 -30.29739 -243.7988
#> [2,] -30.29739 115.98339 -85.6860
#> [3,] -243.79882 -85.68600 329.4848
#>
#> , , 18
#>
#> [,1] [,2] [,3]
#> [1,] 298.22233 -35.60334 -262.61899
#> [2,] -35.60334 133.26429 -97.66096
#> [3,] -262.61899 -97.66096 360.27995
#>
#> , , 19
#>
#> [,1] [,2] [,3]
#> [1,] 324.77085 -43.42878 -281.3421
#> [2,] -43.42878 159.04606 -115.6173
#> [3,] -281.34207 -115.61728 396.9593
#>
#> , , 20
#>
#> [,1] [,2] [,3]
#> [1,] 349.88314 -52.57187 -297.3113
#> [2,] -52.57187 190.29908 -137.7272
#> [3,] -297.31126 -137.72721 435.0385
#>
#> , , 21
#>
#> [,1] [,2] [,3]
#> [1,] 369.39340 -60.52154 -308.8719
#> [2,] -60.52154 220.20491 -159.6834
#> [3,] -308.87186 -159.68337 468.5552
#>
#> , , 22
#>
#> [,1] [,2] [,3]
#> [1,] 380.22632 -64.32675 -315.8996
#> [2,] -64.32675 239.83782 -175.5111
#> [3,] -315.89957 -175.51107 491.4106
#>
#> , , 23
#>
#> [,1] [,2] [,3]
#> [1,] 381.61813 -62.50399 -319.1141
#> [2,] -62.50399 242.93513 -180.4311
#> [3,] -319.11414 -180.43114 499.5453
#>
#> , , 24
#>
#> [,1] [,2] [,3]
#> [1,] 375.59874 -56.21497 -319.3838
#> [2,] -56.21497 230.18569 -173.9707
#> [3,] -319.38377 -173.97072 493.3545
#>
#>
#> $outcomes$chickenPox$icl.pred
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] 28 27 26 26 26 25 25 23 22 20 18 17 15 14
#> [2,] 8 5 4 3 3 3 4 5 6 6 5 4 3 2
#> [3,] 72 75 77 78 76 73 70 67 65 64 66 69 73 76
#> [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
#> [1,] 14 13 13 12 12 11 10 9 8 7
#> [2,] 1 1 1 1 1 1 2 2 1 1
#> [3,] 78 78 76 72 68 65 62 61 62 65
#>
#> $outcomes$chickenPox$icu.pred
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] 74 73 73 74 75 77 78 79 79 78 77 76 74 74
#> [2,] 41 37 35 34 34 37 40 45 49 51 51 49 46 42
#> [3,] 121 125 128 129 130 129 128 127 127 129 132 135 139 142
#> [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
#> [1,] 74 75 76 79 81 82 83 83 82 80
#> [2,] 40 40 41 44 48 53 57 60 60 58
#> [3,] 144 145 146 146 145 145 145 146 148 150
#>
#>
#> $outcomes$show
#> [1] FALSE
#>
#>
#> $theta.mean
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] -1.01019636 -1.03788032 -1.065564268 -1.09324822 -1.12093217 -1.148616125
#> [2,] -0.02768395 -0.02768395 -0.027683953 -0.02768395 -0.02768395 -0.027683953
#> [3,] -0.05892289 -0.09537541 -0.106272170 -0.08869338 -0.04734928 0.006682028
#> [4,] -0.08869338 -0.04734928 0.006682028 0.05892289 0.09537541 0.106272170
#> [5,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [6,] 0.39003624 0.39003624 0.390036237 0.39003624 0.39003624 0.390036237
#> [7,] -2.05310860 -2.08223486 -2.111361115 -2.14048737 -2.16961363 -2.198739882
#> [8,] -0.02912626 -0.02912626 -0.029126256 -0.02912626 -0.02912626 -0.029126256
#> [9,] 0.03653268 -0.14360984 -0.285272227 -0.35049615 -0.32180491 -0.206886307
#> [10,] -0.35049615 -0.32180491 -0.206886307 -0.03653268 0.14360984 0.285272227
#> [11,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [12,] 0.46672032 0.46672032 0.466720323 0.46672032 0.46672032 0.466720323
#> [,7] [,8] [,9] [,10] [,11] [,12]
#> [1,] -1.17630008 -1.20398403 -1.231667983 -1.25935194 -1.28703589 -1.314719841
#> [2,] -0.02768395 -0.02768395 -0.027683953 -0.02768395 -0.02768395 -0.027683953
#> [3,] 0.05892289 0.09537541 0.106272170 0.08869338 0.04734928 -0.006682028
#> [4,] 0.08869338 0.04734928 -0.006682028 -0.05892289 -0.09537541 -0.106272170
#> [5,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [6,] 0.39003624 0.39003624 0.390036237 0.39003624 0.39003624 0.390036237
#> [7,] -2.22786614 -2.25699239 -2.286118649 -2.31524490 -2.34437116 -2.373497416
#> [8,] -0.02912626 -0.02912626 -0.029126256 -0.02912626 -0.02912626 -0.029126256
#> [9,] -0.03653268 0.14360984 0.285272227 0.35049615 0.32180491 0.206886307
#> [10,] 0.35049615 0.32180491 0.206886307 0.03653268 -0.14360984 -0.285272227
#> [11,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [12,] 0.46672032 0.46672032 0.466720323 0.46672032 0.46672032 0.466720323
#> [,13] [,14] [,15] [,16] [,17] [,18]
#> [1,] -1.34240379 -1.37008775 -1.397771698 -1.42545565 -1.45313960 -1.480823556
#> [2,] -0.02768395 -0.02768395 -0.027683953 -0.02768395 -0.02768395 -0.027683953
#> [3,] -0.05892289 -0.09537541 -0.106272170 -0.08869338 -0.04734928 0.006682028
#> [4,] -0.08869338 -0.04734928 0.006682028 0.05892289 0.09537541 0.106272170
#> [5,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [6,] 0.39003624 0.39003624 0.390036237 0.39003624 0.39003624 0.390036237
#> [7,] -2.40262367 -2.43174993 -2.460876183 -2.49000244 -2.51912869 -2.548254950
#> [8,] -0.02912626 -0.02912626 -0.029126256 -0.02912626 -0.02912626 -0.029126256
#> [9,] 0.03653268 -0.14360984 -0.285272227 -0.35049615 -0.32180491 -0.206886307
#> [10,] -0.35049615 -0.32180491 -0.206886307 -0.03653268 0.14360984 0.285272227
#> [11,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [12,] 0.46672032 0.46672032 0.466720323 0.46672032 0.46672032 0.466720323
#> [,19] [,20] [,21] [,22] [,23] [,24]
#> [1,] -1.50850751 -1.53619146 -1.563875413 -1.59155937 -1.61924332 -1.646927271
#> [2,] -0.02768395 -0.02768395 -0.027683953 -0.02768395 -0.02768395 -0.027683953
#> [3,] 0.05892289 0.09537541 0.106272170 0.08869338 0.04734928 -0.006682028
#> [4,] 0.08869338 0.04734928 -0.006682028 -0.05892289 -0.09537541 -0.106272170
#> [5,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [6,] 0.39003624 0.39003624 0.390036237 0.39003624 0.39003624 0.390036237
#> [7,] -2.57738121 -2.60650746 -2.635633716 -2.66475997 -2.69388623 -2.723012483
#> [8,] -0.02912626 -0.02912626 -0.029126256 -0.02912626 -0.02912626 -0.029126256
#> [9,] -0.03653268 0.14360984 0.285272227 0.35049615 0.32180491 0.206886307
#> [10,] 0.35049615 0.32180491 0.206886307 0.03653268 -0.14360984 -0.285272227
#> [11,] 0.00000000 0.00000000 0.000000000 0.00000000 0.00000000 0.000000000
#> [12,] 0.46672032 0.46672032 0.466720323 0.46672032 0.46672032 0.466720323
#>
#> $theta.cov
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 9.559869e-02 1.868326e-03 2.177845e-04 2.520295e-03 0.0000000
#> [2,] 1.868326e-03 4.604931e-04 -3.709447e-05 1.628894e-04 0.0000000
#> [3,] 2.177845e-04 -3.709447e-05 6.451331e-03 1.343320e-04 0.0000000
#> [4,] 2.520295e-03 1.628894e-04 1.343320e-04 6.562663e-03 0.0000000
#> [5,] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.0716381
#> [6,] -6.199776e-02 -8.659647e-07 -6.660636e-04 6.198757e-04 0.0000000
#> [7,] 5.740983e-03 1.057553e-04 1.793818e-04 -4.734687e-06 0.0000000
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#> , , 3
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#> , , 4
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#> , , 5
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#> , , 6
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#>
#> , , 7
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#> [7,] 7.214417e-03 1.401808e-04 -2.040915e-04 -1.416677e-05 0.0000000
#> [8,] 1.398170e-04 5.737582e-06 -4.118280e-06 -3.150242e-06 0.0000000
#> [9,] -2.096218e-04 -4.187968e-06 4.309714e-04 2.915415e-06 0.0000000
#> [10,] -2.296724e-05 -3.353556e-06 2.289083e-06 4.250154e-04 0.0000000
#> [11,] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.0000000
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -6.200295e-02 7.214417e-03 1.398170e-04 -2.096218e-04 -2.296724e-05
#> [2,] -8.659647e-07 1.401808e-04 5.737582e-06 -4.187968e-06 -3.353556e-06
#> [3,] 6.660636e-04 -2.040915e-04 -4.118280e-06 4.309714e-04 2.289083e-06
#> [4,] -6.198757e-04 -1.416677e-05 -3.150242e-06 2.915415e-06 4.250154e-04
#> [5,] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [6,] 6.223498e-02 -3.386250e-03 1.244983e-06 1.125074e-04 -1.144439e-04
#> [7,] -3.386250e-03 1.897554e-01 5.878488e-03 5.196896e-05 -4.508742e-03
#> [8,] 1.244983e-06 5.878488e-03 7.029107e-04 4.712594e-05 -1.967476e-04
#> [9,] 1.125074e-04 5.196896e-05 4.712594e-05 9.219692e-03 1.299627e-04
#> [10,] -1.144439e-04 -4.508742e-03 -1.967476e-04 1.299627e-04 9.453230e-03
#> [11,] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [,11] [,12]
#> [1,] 0.00000000 -3.388569e-03
#> [2,] 0.00000000 1.197936e-06
#> [3,] 0.00000000 1.080394e-04
#> [4,] 0.00000000 -1.108729e-04
#> [5,] 0.00000000 0.000000e+00
#> [6,] 0.00000000 3.426467e-03
#> [7,] 0.00000000 -6.900071e-02
#> [8,] 0.00000000 1.662161e-07
#> [9,] 0.00000000 8.172003e-04
#> [10,] 0.00000000 -7.844873e-04
#> [11,] 0.06747194 0.000000e+00
#>
#> [ reached getOption("max.print") -- omitted 1 row(s) and 17 matrix slice(s) ]
#>
#> $lambda.mean
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] -0.679083 -0.7432195 -0.7818002 -0.7919054 -0.7782452 -0.7518979
#> [2,] -1.549856 -1.7591244 -1.9299130 -2.0242632 -2.0246982 -1.9389059
#> [,7] [,8] [,9] [,10] [,11] [,12]
#> [1,] -0.7273409 -0.7185724 -0.7353596 -0.7806223 -0.8496504 -0.9313656
#> [2,] -1.7976785 -1.6466622 -1.5341261 -1.4980284 -1.5558459 -1.6998908
#> [,13] [,14] [,15] [,16] [,17] [,18] [,19]
#> [1,] -1.011290 -1.075427 -1.114008 -1.124113 -1.110453 -1.084105 -1.059548
#> [2,] -1.899371 -2.108639 -2.279428 -2.373778 -2.374213 -2.288421 -2.147194
#> [,20] [,21] [,22] [,23] [,24]
#> [1,] -1.050780 -1.067567 -1.112830 -1.181858 -1.263573
#> [2,] -1.996177 -1.883641 -1.847543 -1.905361 -2.049406
#>
#> $lambda.cov
#> , , 1
#>
#> [,1] [,2]
#> [1,] 0.111031031 0.002952275
#> [2,] 0.002952275 0.114880251
#>
#> , , 2
#>
#> [,1] [,2]
#> [1,] 0.123672883 0.003275323
#> [2,] 0.003275323 0.130104017
#>
#> , , 3
#>
#> [,1] [,2]
#> [1,] 0.136830380 0.003541592
#> [2,] 0.003541592 0.145910042
#>
#> , , 4
#>
#> [,1] [,2]
#> [1,] 0.149593768 0.003738337
#> [2,] 0.003738337 0.161078684
#>
#> , , 5
#>
#> [,1] [,2]
#> [1,] 0.161467867 0.003876132
#> [2,] 0.003876132 0.174921870
#>
#> , , 6
#>
#> [,1] [,2]
#> [1,] 0.172493799 0.003984471
#> [2,] 0.003984471 0.187492253
#>
#> , , 7
#>
#> [,1] [,2]
#> [1,] 0.183192092 0.004103871
#> [2,] 0.004103871 0.199515810
#>
#> , , 8
#>
#> [,1] [,2]
#> [1,] 0.194434525 0.004277022
#> [2,] 0.004277022 0.212174787
#>
#> , , 9
#>
#> [,1] [,2]
#> [1,] 0.207308809 0.004539212
#> [2,] 0.004539212 0.226871186
#>
#> , , 10
#>
#> [,1] [,2]
#> [1,] 0.222942264 0.004908079
#> [2,] 0.004908079 0.244987991
#>
#> , , 11
#>
#> [,1] [,2]
#> [1,] 0.242227680 0.005375258
#> [2,] 0.005375258 0.267588593
#>
#> , , 12
#>
#> [,1] [,2]
#> [1,] 0.265491167 0.005904707
#> [2,] 0.005904707 0.295057987
#>
#> , , 13
#>
#> [,1] [,2]
#> [1,] 0.292266282 0.006441238
#> [2,] 0.006441238 0.326834106
#>
#> , , 14
#>
#> [,1] [,2]
#> [1,] 0.321351876 0.006927658
#> [2,] 0.006927658 0.361440228
#>
#> , , 15
#>
#> [,1] [,2]
#> [1,] 0.351188944 0.007323712
#> [2,] 0.007323712 0.396907427
#>
#> , , 16
#>
#> [,1] [,2]
#> [1,] 0.380397001 0.007618777
#> [2,] 0.007618777 0.431442027
#>
#> , , 17
#>
#> [,1] [,2]
#> [1,] 0.408221257 0.007833981
#> [2,] 0.007833981 0.464034915
#>
#> , , 18
#>
#> [,1] [,2]
#> [1,] 0.434723899 0.008014972
#> [2,] 0.008014972 0.494756726
#>
#> , , 19
#>
#> [,1] [,2]
#> [1,] 0.460721555 0.008219696
#> [2,] 0.008219696 0.524685622
#>
#> , , 20
#>
#> [,1] [,2]
#> [1,] 0.487577799 0.008504881
#> [2,] 0.008504881 0.555595865
#>
#> , , 21
#>
#> [,1] [,2]
#> [1,] 0.51693605 0.00891269
#> [2,] 0.00891269 0.58956268
#>
#> , , 22
#>
#> [,1] [,2]
#> [1,] 0.55039436 0.00945864
#> [2,] 0.00945864 0.62854309
#>
#> , , 23
#>
#> [,1] [,2]
#> [1,] 0.58910514 0.01012381
#> [2,] 0.01012381 0.67392152
#>
#> , , 24
#>
#> [,1] [,2]
#> [1,] 0.63337341 0.01085602
#> [2,] 0.01085602 0.72606499
#>
#>
#> $plot
#>