GOF for CMPLE method. Available soon?

[EffeBi-CH]

I am estimating a tergm with the CMPLE method. Unfortunately, the CMLE methods does not seem an option. If this feature will not be available soon, do you have suggestions on how to implement it? Thanks.

[krivit]

I don't have time to test this on the CRAN version, but the current version in master seems to work:

library(tergm)
data(samplk)
samplk12 <- tergm(list(samplk1, samplk2) ~ 
  Form(~edges+mutual+transitiveties+cyclicalties) +
  Diss(~edges+mutual+transitiveties+cyclicalties),
  estimate="CMPLE")
samplk12.gof <- gof(samplk12)
print(samplk12.gof)
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.
#> Evaluating log-likelihood at the estimate.
#> 
#> Goodness-of-fit for in-degree 
#> 
#>           obs min mean max MC p-value
#> idegree0    0   0 0.61   3       1.00
#> idegree1    3   0 2.67   7       1.00
#> idegree2    8   1 4.10   9       0.08
#> idegree3    2   0 3.97   9       0.48
#> idegree4    1   0 2.81   7       0.36
#> idegree5    1   0 1.83   5       0.84
#> idegree6    0   0 1.17   4       0.54
#> idegree7    1   0 0.43   2       0.70
#> idegree8    2   0 0.24   2       0.04
#> idegree9    0   0 0.16   1       1.00
#> idegree10   0   0 0.01   1       1.00
#> 
#> Goodness-of-fit for out-degree 
#> 
#>           obs min mean max MC p-value
#> odegree0    0   0 0.18   2       1.00
#> odegree1    0   0 1.54   5       0.52
#> odegree2    0   0 4.40   9       0.04
#> odegree3   15   1 5.26  11       0.00
#> odegree4    3   0 3.94  10       0.84
#> odegree5    0   0 1.68   5       0.36
#> odegree6    0   0 0.72   3       0.88
#> odegree7    0   0 0.20   4       1.00
#> odegree8    0   0 0.07   1       1.00
#> odegree10   0   0 0.01   1       1.00
#> 
#> Goodness-of-fit for edgewise shared partner 
#> 
#>          obs min  mean max MC p-value
#> esp.OTP0  27  22 32.76  44       0.28
#> esp.OTP1  19   8 18.41  32       0.94
#> esp.OTP2   7   0  4.68  16       0.52
#> esp.OTP3   4   0  0.68   5       0.08
#> esp.OTP4   0   0  0.11   1       1.00
#> esp.OTP6   0   0  0.02   1       1.00
#> 
#> Goodness-of-fit for minimum geodesic distance 
#> 
#>     obs min   mean max MC p-value
#> 1    57  39  56.66  74       1.00
#> 2    85  59 103.62 144       0.36
#> 3    81  54  83.16 113       0.82
#> 4    41   9  32.02  55       0.42
#> 5    17   0   8.91  32       0.30
#> 6    12   0   2.24  17       0.08
#> 7    10   0   0.53  10       0.02
#> 8     3   0   0.12   7       0.02
#> 9     0   0   0.02   2       1.00
#> Inf   0   0  18.72 115       0.76
#> 
#> Goodness-of-fit for model statistics 
#> 
#>                        obs min   mean max MC p-value
#> Form(1)~edges           77  64  77.06  92       1.00
#> Form(1)~mutual          24  17  23.42  30       0.98
#> Form(1)~transitiveties  52  29  50.25  73       0.90
#> Form(1)~cyclicalties    46  21  42.85  66       0.86
#> Diss(1)~edges          -35 -47 -34.60 -26       0.88
#> Diss(1)~mutual          -8 -13  -7.58  -2       1.00
#> Diss(1)~transitiveties  -6  -9  -3.32   0       0.36
#> Diss(1)~cyclicalties    -3 -12  -2.85   0       1.00

^{Created on 2023-05-13 with reprex v2.0.2}

Is this what you are looking for?

[EffeBi-CH]

Yes, thank you! I used to get the following error message: "Error in gof.default(fit) : Goodness-of-Fit methods have been implemented only for class(es) "ergm", "formula", and "tergm_EGMME" in the packages loaded." Now it works fine.