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> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
> 
> library(testthat)
> library(seqHMM)
Please cite seqHMM in publications by using: 

  Helske S, Helske J (2019). Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R. Journal of
Statistical Software, 88(3), 1-32. doi: 10.18637/jss.v088.i03.
> 
> test_check("seqHMM")
 [>] 4 distinct states appear in the data: 
     1 = a
     2 = b
     3 = c
     4 = d
 [>] state coding:
       [alphabet]  [label]  [long label] 
     1  a           a        a
     2  b           b        b
     3  c           c        c
     4  d           d        d
 [>] 5 sequences in the data set
 [>] min/max sequence length: 10/10
 [>] 4 distinct states appear in the data: 
     1 = a
     2 = b
     3 = c
     4 = d
 [>] state coding:
       [alphabet]  [label]  [long label] 
     1  a           a        a
     2  b           b        b
     3  c           c        c
     4  d           d        d
 [>] 5 sequences in the data set
 [>] min/max sequence length: 10/10
 [>] 5 distinct states appear in the data: 
     1 = a
     2 = b
     3 = c
     4 = d
     5 = e
 [>] state coding:
       [alphabet]  [label]  [long label] 
     1  a           a        a
     2  b           b        b
     3  c           c        c
     4  d           d        d
     5  e           e        e
 [>] 5 sequences in the data set
 [>] min/max sequence length: 10/10
 [>] 4 distinct states appear in the data: 
     1 = a
     2 = b
     3 = c
     4 = d
 [>] state coding:
       [alphabet]  [label]  [long label] 
     1  a           a        a
     2  b           b        b
     3  c           c        c
     4  d           d        d
 [>] 5 sequences in the data set
 [>] min/max sequence length: 10/10
 [>] 5 distinct states appear in the data: 
     1 = a
     2 = b
     3 = c
     4 = d
     5 = e
 [>] state coding:
       [alphabet]  [label]  [long label] 
     1  a           a        a
     2  b           b        b
     3  c           c        c
     4  d           d        d
     5  e           e        e
 [>] 5 sequences in the data set
 [>] min/max sequence length: 10/10
Initial probabilities :
State 1 State 2 
      1       0 

Transition probabilities :
         to
from      State 1 State 2
  State 1   0.715   0.285
  State 2   0.277   0.723

Emission probabilities :
           symbol_names
state_names      1     2
    State 1 0.5725 0.428
    State 2 0.0816 0.918

Coefficients :
             Cluster 1 Cluster 2
(Intercept)          0     -1.10
covariate_1          0      3.82
covariate_2B         0     -1.98

Initial probabilities :
Cluster 1 :
coin 1 coin 2 
     1      0 

Cluster 2 :
coin 3 coin 4 
     1      0 

Transition probabilities :
Cluster 1 :
        to
from     coin 1 coin 2
  coin 1  0.867  0.133
  coin 2  0.000  1.000

Cluster 2 :
        to
from     coin 3 coin 4
  coin 3  0.969 0.0306
  coin 4  0.029 0.9710

Emission probabilities :
Cluster 1 :
        heads tails
coin 1 0.7457 0.254
coin 2 0.0486 0.951

Cluster 2 :
        heads tails
coin 3 0.0829 0.917
coin 4 0.7905 0.209


[ FAIL 0 | WARN 0 | SKIP 0 | PASS 88 ]
> 
> proc.time()
   user  system elapsed 
   3.89    0.50    4.39