Running examples in ‘hdpGLM-Ex.R’ failed
The error most likely occurred in:

> ### Name: plot_hdpglm
> ### Title: Plot posterior distributions
> ### Aliases: plot_hdpglm
> 
> ### ** Examples
> 
> 
> library(magrittr)
> # Note: this example is just for illustration. MCMC iterations are very reduced
> set.seed(10)
> n = 20
> data.context1 = tibble::tibble(x1 = rnorm(n, -3),
+                                    x2 = rnorm(n,  3),
+                                    z  = sample(1:3, n, replace=TRUE),
+                                    y  =I(z==1) * (3 + 4*x1 - x2 + rnorm(n)) +
+                                        I(z==2) * (3 + 2*x1 + x2 + rnorm(n)) +
+                                        I(z==3) * (3 - 4*x1 - x2 + rnorm(n)) ,
+                                    w = 20
+                                    ) 
> data.context2 = tibble::tibble(x1 = rnorm(n, -3),
+                                    x2 = rnorm(n,  3),
+                                    z  = sample(1:2, n, replace=TRUE),
+                                    y  =I(z==1) * (1 + 3*x1 - 2*x2 + rnorm(n)) +
+                                        I(z==2) * (1 - 2*x1 +   x2 + rnorm(n)),
+                                    w = 10
+                                    ) 
> data = data.context1 %>%
+     dplyr::bind_rows(data.context2)
> 
> ## estimation
> mcmc    = list(burn.in=1, n.iter=50)
> samples = hdpGLM(y ~ x1 + x2, y ~ w, data=data, mcmc=mcmc, n.display=1)


Preparing for estimation ...



Estimation in progress ...



-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 1

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 1
Maximum Number of Clusters Active in the Current Iteration : 1

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
   1.0000e+00
   1.0000e+02

Clusters in Context 2
    1.0000
   95.0000

[===                                                                    ] 3 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 2

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 2
Maximum Number of Clusters Active in the Current Iteration : 2

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000
   25.0000   75.0000

Clusters in Context 2
    1.0000    3.0000    4.0000
   10.0000   55.0000   35.0000

[=====                                                                  ] 5 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 3

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 4
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    5.0000
   15.0000   10.0000   40.0000   35.0000

Clusters in Context 2
    1.0000    2.0000    3.0000    4.0000    7.0000
   10.0000   30.0000   30.0000   10.0000   15.0000

[======                                                                 ] 7 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 4

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 6
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    2.0000    4.0000    5.0000    7.0000
   10.0000   35.0000   10.0000   35.0000

Clusters in Context 2
    3.0000    4.0000    5.0000    7.0000
   35.0000   15.0000   20.0000   15.0000

[=======                                                                ] 9 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 5

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 8
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    4.0000    5.0000    6.0000
   10.0000   35.0000   10.0000   10.0000   20.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   40.0000

[=========                                                              ] 11 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 6

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 9

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    2.0000    3.0000    5.0000    6.0000    7.0000    8.0000
   15.0000   10.0000   10.0000   15.0000   10.0000   25.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   40.0000

[==========                                                             ] 13 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 7

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    2.0000    3.0000    4.0000    5.0000    6.0000   11.0000
   20.0000   10.0000   15.0000   15.0000   20.0000   10.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   40.0000

[===========                                                            ] 15 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 8

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 7

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    4.0000    5.0000    6.0000
   15.0000   10.0000   15.0000   25.0000   25.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   45.0000

[=============                                                          ] 17 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 9

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    2.0000    4.0000    5.0000    6.0000
   10.0000   20.0000   10.0000   40.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   45.0000

[==============                                                         ] 19 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 10

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 9

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    2.0000    4.0000    5.0000    6.0000
   15.0000   15.0000   10.0000   35.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   40.0000

[================                                                       ] 21 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 11

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    4.0000    6.0000    7.0000   10.0000
   15.0000   15.0000   35.0000   10.0000   10.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   50.0000

[=================                                                      ] 23 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 12

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    4.0000    6.0000    7.0000    9.0000
   15.0000   40.0000   15.0000   10.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   50.0000

[==================                                                     ] 25 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 13

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    4.0000    6.0000    7.0000
   10.0000   15.0000   45.0000   10.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   50.0000

[====================                                                   ] 27 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 14

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 8

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    4.0000    6.0000    7.0000
   10.0000   10.0000   15.0000   40.0000   10.0000

Clusters in Context 2
    3.0000    7.0000
   45.0000   45.0000

[=====================                                                  ] 29 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 15

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    4.0000    6.0000
   20.0000   10.0000   15.0000   50.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   45.0000

[======================                                                 ] 31 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 16

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    4.0000    6.0000
   20.0000   15.0000   50.0000

Clusters in Context 2
    3.0000    7.0000
   50.0000   45.0000

[========================                                               ] 33 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 17

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    4.0000    5.0000    6.0000
   10.0000   10.0000   10.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   10.0000   50.0000   40.0000

[=========================                                              ] 35 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 18

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   10.0000   20.0000   10.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   10.0000   50.0000   40.0000

[===========================                                            ] 37 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 19

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 7

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000    7.0000
   10.0000   15.0000   10.0000   45.0000   10.0000

Clusters in Context 2
    1.0000    3.0000    6.0000    7.0000
   10.0000   50.0000   10.0000   30.0000

[============================                                           ] 39 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 20

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 7

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    5.0000    6.0000
   15.0000   10.0000   15.0000   45.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   10.0000   50.0000   35.0000

[=============================                                          ] 41 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 21

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    4.0000    6.0000
   20.0000   10.0000   10.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   10.0000   45.0000   40.0000

[===============================                                        ] 43 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 22

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    6.0000
   20.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   10.0000   50.0000   40.0000

[================================                                       ] 45 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 23

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   25.0000   10.0000   10.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   15.0000   50.0000   35.0000

[=================================                                      ] 47 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 24

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000    6.0000
   20.0000   10.0000   10.0000   10.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   15.0000   50.0000   35.0000

[===================================                                    ] 49 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 25

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   25.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   25.0000   40.0000   25.0000

[====================================                                   ] 50 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 26

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   25.0000   10.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000    7.0000
   35.0000   45.0000   15.0000

[======================================                                 ] 52 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 27

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   25.0000   10.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   45.0000   45.0000

[=======================================                                ] 54 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 28

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    4.0000    6.0000
   20.0000   15.0000   10.0000   45.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[========================================                               ] 56 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 29

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   20.0000   10.0000   10.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   45.0000   50.0000

[==========================================                             ] 58 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 30

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   15.0000   10.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[===========================================                            ] 60 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 31

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   25.0000   15.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[============================================                           ] 62 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 32

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   20.0000   20.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[==============================================                         ] 64 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 33

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   15.0000   20.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[===============================================                        ] 66 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 34

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   25.0000   20.0000   50.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   45.0000

[=================================================                      ] 68 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 35

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   25.0000   25.0000   45.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[==================================================                     ] 70 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 36

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   25.0000   25.0000   45.0000

Clusters in Context 2
    1.0000    3.0000
   45.0000   50.0000

[===================================================                    ] 72 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 37

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    6.0000
   20.0000   25.0000   45.0000

Clusters in Context 2
    1.0000    2.0000    3.0000
   40.0000   10.0000   50.0000

[=====================================================                  ] 74 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 38

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    3.0000    5.0000    6.0000
   20.0000   30.0000   10.0000   40.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[======================================================                 ] 76 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 39

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    6.0000
   20.0000   10.0000   25.0000   40.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[=======================================================                ] 78 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 40

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 7

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000    6.0000
   10.0000   20.0000   15.0000   15.0000   30.0000

Clusters in Context 2
    1.0000    3.0000
   45.0000   50.0000

[=========================================================              ] 80 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 41

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 5

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   15.0000   45.0000   20.0000   15.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[==========================================================             ] 82 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 42

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000    6.0000
   15.0000   35.0000   20.0000   15.0000   10.0000

Clusters in Context 2
    1.0000    2.0000    3.0000
   45.0000   10.0000   45.0000

[============================================================           ] 84 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 43

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   15.0000   40.0000   20.0000   15.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[=============================================================          ] 86 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 44

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 6

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   10.0000   45.0000   20.0000   15.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[==============================================================         ] 88 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 45

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   10.0000   50.0000   20.0000   20.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[================================================================       ] 90 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 46

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   15.0000   50.0000   20.0000   15.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   45.0000

[=================================================================      ] 92 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 47

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   10.0000   50.0000   20.0000   20.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[==================================================================     ] 94 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 48

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000    4.0000
   15.0000   50.0000   25.0000   10.0000

Clusters in Context 2
    1.0000    3.0000
   45.0000   50.0000

[====================================================================   ] 96 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 49

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000
   25.0000   50.0000   20.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[=====================================================================  ] 98 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 50

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000
   20.0000   50.0000   25.0000

Clusters in Context 2
    1.0000    3.0000
   50.0000   50.0000

[=======================================================================] 100 %

-----------------------------------------------------
MCMC in progress ....

Family of the distribution of the outcome variable of the mixture components: gaussian

Burn-in: 1
Number of MCMC Iterations : 50

Iteration: 51

Acceptance Rate for beta         : 1
Average Acceptance Rate for beta : 1

Maximum Number of Clusters Allowed (K)                      : 100
Maximum Number of Clusters Activated Among All Contexts     : 9
Maximum Number of Clusters Active in the Current Iteration : 4

(displaying only clusters with more than 5% of the data)
Clusters in Context 1
    1.0000    2.0000    3.0000
   25.0000   50.0000   20.0000

Clusters in Context 2
    1.0000    3.0000
   45.0000   50.0000

[=======================================================================] 100 %
> 
> plot_hdpglm(samples)


Plot being generated ...



Generating plots ...

Warning: The `<scale>` argument of `guides()` cannot be `FALSE`. Use "none" instead as
of ggplot2 3.3.4.
ℹ The deprecated feature was likely used in the hdpGLM package.
  Please report the issue at <https://github.com/DiogoFerrari/hdpGLM/issues>.
> plot_hdpglm(samples, ncol.taus=2, ncol.betas=2, X='x1')


Plot being generated ...



Generating plots ...

> plot_hdpglm(samples, ncol.taus=2, ncol.betas=2, X='x1', ncol.w=2, nrow.w=1,
+             pred.pexp.beta=TRUE,smooth.line=TRUE )


Plot being generated ...



Generating plots ...

`geom_smooth()` using formula = 'y ~ x'

 *** caught segfault ***
address 0x4, cause 'memory not mapped'
*** recursive gc invocation
*** recursive gc invocation
*** recursive gc invocation
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Traceback:
 1: getGeneric(what, FALSE, where)
 2: .recMembers(members, .methodsNamespace)
 3: getGroupMembers(fdef, TRUE, FALSE)
 4: .checkGroupSigLength(groups, generics)
 5: .updateMethodsInTable(getGeneric(g), where, attach)
 6: .updateMethodsInTable(fdef, where, attach)
 7: methods::cacheMetaData(ns, TRUE, ns)
 8: loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
 9: asNamespace(ns)
10: namespaceImportFrom(ns, loadNamespace(j <- i[[1L]], c(lib.loc,     .libPaths()), versionCheck = vI[[j]]), i[[2L]], from = package)
11: loadNamespace(x)
12: gam_method()
13: compute_group(...)
14: self$compute_group(data = group, scales = scales, ...)
15: FUN(X[[i]], ...)
16: lapply(groups, function(group) {    self$compute_group(data = group, scales = scales, ...)})
17: compute_panel(..., self = self)
18: self$compute_panel(data = data, scales = scales, na.rm = FALSE,     se = TRUE, method = "lm", flipped_aes = FALSE, formula = y ~         x)
19: inject(self$compute_panel(data = data, scales = scales, !!!params))
20: withCallingHandlers(expr, condition = function(cnd) {    {        .__handler_frame__. <- TRUE        .__setup_frame__. <- frame        if (inherits(cnd, "message")) {            except <- c("warning", "error")        }        else if (inherits(cnd, "warning")) {            except <- "error"        }        else {            except <- ""        }    }    while (!is_null(cnd)) {        if (inherits(cnd, "error")) {            out <- handlers[[1L]](cnd)            if (!inherits(out, "rlang_zap"))                 throw(out)        }        inherit <- .subset2(.subset2(cnd, "rlang"), "inherit")        if (is_false(inherit)) {            return()        }        cnd <- .subset2(cnd, "parent")    }})
21: doTryCatch(return(expr), name, parentenv, handler)
22: tryCatchOne(expr, names, parentenv, handlers[[1L]])
23: tryCatchList(expr, classes, parentenv, handlers)
24: tryCatch(withCallingHandlers(expr, condition = function(cnd) {    {        .__handler_frame__. <- TRUE        .__setup_frame__. <- frame        if (inherits(cnd, "message")) {            except <- c("warning", "error")        }        else if (inherits(cnd, "warning")) {            except <- "error"        }        else {            except <- ""        }    }    while (!is_null(cnd)) {        if (inherits(cnd, "error")) {            out <- handlers[[1L]](cnd)            if (!inherits(out, "rlang_zap"))                 throw(out)        }        inherit <- .subset2(.subset2(cnd, "rlang"), "inherit")        if (is_false(inherit)) {            return()        }        cnd <- .subset2(cnd, "parent")    }}), stackOverflowError = handlers[[1L]])
25: try_fetch(inject(self$compute_panel(data = data, scales = scales,     !!!params)), error = function(cnd) {    cli::cli_warn("Computation failed in {.fn {snake_class(self)}}",         parent = cnd)    data_frame0()})
26: fun(x, ...)
27: apply_fun(df)
28: dapply(data, "PANEL", function(data) {    scales <- layout$get_scales(data$PANEL[1])    try_fetch(inject(self$compute_panel(data = data, scales = scales,         !!!params)), error = function(cnd) {        cli::cli_warn("Computation failed in {.fn {snake_class(self)}}",             parent = cnd)        data_frame0()    })})
29: compute_layer(..., self = self)
30: self$stat$compute_layer(data, self$computed_stat_params, layout)
31: compute_statistic(..., self = self)
32: l$compute_statistic(d, layout)
33: f(l = layers[[i]], d = data[[i]])
34: withCallingHandlers(expr, condition = function(cnd) {    {        .__handler_frame__. <- TRUE        .__setup_frame__. <- frame        if (inherits(cnd, "message")) {            except <- c("warning", "error")        }        else if (inherits(cnd, "warning")) {            except <- "error"        }        else {            except <- ""        }    }    while (!is_null(cnd)) {        if (inherits(cnd, "error")) {            out <- handlers[[1L]](cnd)            if (!inherits(out, "rlang_zap"))                 throw(out)        }        inherit <- .subset2(.subset2(cnd, "rlang"), "inherit")        if (is_false(inherit)) {            return()        }        cnd <- .subset2(cnd, "parent")    }})
35: doTryCatch(return(expr), name, parentenv, handler)
36: tryCatchOne(expr, names, parentenv, handlers[[1L]])
37: tryCatchList(expr, classes, parentenv, handlers)
38: tryCatch(withCallingHandlers(expr, condition = function(cnd) {    {        .__handler_frame__. <- TRUE        .__setup_frame__. <- frame        if (inherits(cnd, "message")) {            except <- c("warning", "error")        }        else if (inherits(cnd, "warning")) {            except <- "error"        }        else {            except <- ""        }    }    while (!is_null(cnd)) {        if (inherits(cnd, "error")) {            out <- handlers[[1L]](cnd)            if (!inherits(out, "rlang_zap"))                 throw(out)        }        inherit <- .subset2(.subset2(cnd, "rlang"), "inherit")        if (is_false(inherit)) {            return()        }        cnd <- .subset2(cnd, "parent")    }}), stackOverflowError = handlers[[1L]])
39: try_fetch(for (i in seq_along(data)) {    out[[i]] <- f(l = layers[[i]], d = data[[i]])}, error = function(cnd) {    cli::cli_abort(c("Problem while {step}.", i = "Error occurred in the {ordinal(i)} layer."),         call = layers[[i]]$constructor, parent = cnd)})
40: by_layer(function(l, d) l$compute_statistic(d, layout), layers,     data, "computing stat")
41: ggplot_build.ggplot(p)
42: ggplot_build(p)
43: options(ggplot2_plot_env = env)
44: attach_plot_env(data$plot$plot_env)
45: ggplot_gtable(ggplot_build(p))
46: .get_legend(p[[i]], position = position)
47: get_legend(plots)
48: ggpubr::ggarrange(plotlist = plots, nrow = nrow.w, ncol = ncol.w,     common.legend = T, legend = legend.position)
49: plot_pexp_beta(samples, X = X, W = W, ncol.beta = ncol.betas,     ncol.w = ncol.w, nrow.w = nrow.w, smooth.line = smooth.line,     pred.pexp.beta = pred.pexp.beta, title = title.beta, x.axis.size = beta.x.axis.size,     y.axis.size = beta.y.axis.size, title.size = beta.title.size,     panel.title.size = beta.panel.title.size, legend.size = beta.legend.size)
50: plot_hdpglm(samples, ncol.taus = 2, ncol.betas = 2, X = "x1",     ncol.w = 2, nrow.w = 1, pred.pexp.beta = TRUE, smooth.line = TRUE)
An irrecoverable exception occurred. R is aborting now ...