R Under development (unstable) (2023-12-02 r85657 ucrt) -- "Unsuffered Consequences"
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> library(ordinal)
> 
> 
> ## Testing that errors in chol() are caught soon enough:
> cy <- with(wine, which(temp == "cold" & contact == "yes"))
> wine2 <- subset(wine, subset=(!1:nrow(wine) %in% cy))
> wine2[c(9, 15, 46), "rating"] <- NA
> fm1 <- clm(rating ~ temp, scale=~contact, nominal=~contact,
+            data=wine2)
Warning message:
(1) Hessian is numerically singular: parameters are not uniquely determined 
In addition: Absolute convergence criterion was met, but relative criterion was not met 
> fm1 <- try(clm(rating ~ temp, scale=~contact, nominal=~contact,
+                data=wine2, control=list(gradTol=1e-12)), silent=TRUE)
Warning message:
(1) Hessian is numerically singular: parameters are not uniquely determined 
In addition: Absolute convergence criterion was met, but relative criterion was not met 
> fm2 <- try(clm(rating ~ temp, scale=~contact, nominal=~contact,
+                data=wine2, control=list(gradTol=1e-15)), silent=TRUE)
Warning message:
(-1) Model failed to converge with max|grad| = 1.11481e-07 (tol = 1e-15) 
In addition: iteration limit reached 
> ## These gave errors in version 2014.11-12.
> stopifnot(!inherits(fm1, "try-error"))
> stopifnot(!inherits(fm2, "try-error"))
> summary(fm1)
formula: rating ~ temp
scale:   ~contact
nominal: ~contact
data:    wine2

 link  threshold nobs logLik AIC    niter  max.grad cond.H  
 logit flexible  51   -60.44 140.87 63(39) 1.51e-13 -2.1e+16

Coefficients:
         Estimate Std. Error z value Pr(>|z|)
tempwarm    2.306         NA      NA       NA

log-scale coefficients:
           Estimate Std. Error z value Pr(>|z|)
contactyes -0.07119         NA      NA       NA

Threshold coefficients:
                Estimate Std. Error z value
1|2.(Intercept)   -1.354         NA      NA
2|3.(Intercept)    1.092         NA      NA
3|4.(Intercept)    3.469         NA      NA
4|5.(Intercept)    5.066         NA      NA
1|2.contactyes   -30.684         NA      NA
2|3.contactyes    -1.425         NA      NA
3|4.contactyes    -1.808         NA      NA
4|5.contactyes    -1.870         NA      NA
(3 observations deleted due to missingness)
> summary(fm2)
formula: rating ~ temp
scale:   ~contact
nominal: ~contact
data:    wine2

 link  threshold nobs logLik AIC    niter   max.grad cond.H 
 logit flexible  51   -60.44 140.87 111(86) 1.11e-07 1.8e+17

Coefficients:
         Estimate Std. Error z value Pr(>|z|)   
tempwarm   2.3060     0.7713    2.99  0.00279 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

log-scale coefficients:
             Estimate Std. Error z value Pr(>|z|)
contactyes   -0.07126 2995.02357       0        1

Threshold coefficients:
                  Estimate Std. Error z value
1|2.(Intercept) -1.354e+00  5.707e-01  -2.373
2|3.(Intercept)  1.092e+00  5.251e-01   2.080
3|4.(Intercept)  3.469e+00  7.982e-01   4.346
4|5.(Intercept)  5.066e+00  1.193e+00   4.246
1|2.contactyes  -3.822e+01  1.282e+09   0.000
2|3.contactyes  -1.425e+00  7.902e+03   0.000
3|4.contactyes  -1.808e+00  1.933e+03  -0.001
4|5.contactyes  -1.870e+00  2.665e+03  -0.001
(3 observations deleted due to missingness)
> 
> ## Error in convergence.clm() due to bad evaluation of model
> ## environment with update(object, doFit=FALSE):
> wine3 <- wine
> set.seed(1234)
> wts <- runif(nrow(wine3), 0, 2)
> fm3 <- clm(rating ~ temp + contact, data=wine3,
+            weights=wts)
> c0 <- convergence(fm3)
> set.seed(1234)
> fm3 <- clm(rating ~ temp + contact, data=wine3,
+            weights=runif(nrow(wine3), 0, 2))
> c1 <- convergence(fm3)
> c0$info$logLik.Error
[1] "<1e-10"
> c1$info$logLik.Error
[1] "<1e-10"
> all.equal(c0$info$logLik.Error, c1$info$logLik.Error)
[1] TRUE
> ## In version 2014.11-14:
> ## > wine3 <- wine
> ## > set.seed(1234)
> ## > wts <- runif(nrow(wine3), 0, 2)
> ## > fm3 <- clm(rating ~ temp + contact, data=wine3,
> ## +            weights=wts)
> ## > c0 <- convergence(fm3)
> ## > set.seed(1234)
> ## > fm3 <- clm(rating ~ temp + contact, data=wine3,
> ## +            weights=runif(nrow(wine3), 0, 2))
> ## > c1 <- convergence(fm3)
> ## > c0$info$logLik.Error
> ## [1] "<1e-10"
> ## > c1$info$logLik.Error
> ## [1] "4.80e+00"
> ## > all.equal(c0$info$logLik.Error, c1$info$logLik.Error)
> ## [1] "1 string mismatch"
> stopifnot(c0$info$logLik.Error ==
+           c1$info$logLik.Error)
> 
> proc.time()
   user  system elapsed 
   1.54    0.28    1.81