R Under development (unstable) (2023-06-29 r84618 ucrt) -- "Unsuffered Consequences"
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> 
> library("MASS")
> 
> mp <- polr(Sat ~ Infl, weights = Freq, data = housing)
> 
> library("mlt")
Loading required package: basefun
Loading required package: variables
> 
> s <- as.basis(~ Infl, data = housing, remove_intercept = TRUE)
> r <- as.basis(housing$Sat)
> #r <- as.basis(~ Sat, data = housing, remove_intercept = TRUE,
> #              contrasts.arg = list(Sat = function(n) 
> #                  contr.treatment(n, base = 3)),
> #              ui = diff(diag(2)), ci = 0)
> 
> m <- ctm(r, shift = s, todist = "Logi")
> 
> mod <- mlt(m, data = housing, weights = housing$Freq)
> 
> logLik(mp)
'log Lik.' -1771.708 (df=4)
> logLik(mod)
'log Lik.' -1771.708 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
 0.5635756  1.2486832 
> mp$zeta
 Low|Medium Medium|High 
 -0.2013727   0.9484658 
> ### PR#17616
> unname(coef(mod))
[1] -0.2013745  0.9484782 -0.5635842 -1.2486779
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
 0.10357053  0.12479361  0.07662596  0.08024304 
> unname(sqrt(diag(vcov(mod))))
[1] 0.07662595 0.08024303 0.10357053 0.12479363
> 
> mp <- polr(Sat ~ Infl, weights = Freq, data = housing, method = "loglog")
> 
> s <- as.basis(~ Infl, data = housing, remove_intercept = TRUE)
> r <- as.basis(housing$Sat)
> m <- ctm(r, shift = s, todist = "MaxExtrVal")
> 
> mod <- mlt(m, data = housing, weights = housing$Freq)
> 
> logLik(mp)
'log Lik.' -1776.416 (df=4)
> logLik(mod)
'log Lik.' -1776.416 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
 0.3851078  0.7837681 
> mp$zeta
 Low|Medium Medium|High 
  0.2425732   1.0315129 
> unname(coef(mod))
[1]  0.2425772  1.0315177 -0.3851189 -0.7837785
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
 0.07219408  0.07953692  0.05453940  0.06090649 
> unname(sqrt(diag(vcov(mod))))
[1] 0.05453958 0.06090668 0.07219424 0.07953700
> 
> mp <- polr(Sat ~ Infl, weights = Freq, data = housing, method = "cloglog")
> 
> s <- as.basis(~ Infl, data = housing, remove_intercept = TRUE)
> r <- as.basis(housing$Sat)
> m <- ctm(r, shift = s, todist = "MinExtrVal")
> 
> mod <- mlt(m, data = housing, weights = housing$Freq)
> 
> logLik(mp)
'log Lik.' -1772.924 (df=4)
> logLik(mod)
'log Lik.' -1772.924 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
 0.3662567  0.8792058 
> mp$zeta
 Low|Medium Medium|High 
 -0.5679040   0.2655082 
> unname(coef(mod))
[1] -0.5679043  0.2655074 -0.3662565 -0.8792066
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
 0.06980195  0.09157487  0.05441248  0.04894207 
> unname(sqrt(diag(vcov(mod))))
[1] 0.05441250 0.04894209 0.06980196 0.09157492
> 
> mp <- polr(Sat ~ Infl, weights = Freq, data = housing, method = "probit")
> 
> s <- as.basis(~ Infl, data = housing, remove_intercept = TRUE)
> r <- as.basis(housing$Sat)
> m <- ctm(r, shift = s, todist = "Normal")
> 
> mod <- mlt(m, data = housing, weights = housing$Freq)
> 
> logLik(mp)
'log Lik.' -1772.056 (df=4)
> logLik(mod)
'log Lik.' -1772.056 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
 0.3465900  0.7608878 
> mp$zeta
 Low|Medium Medium|High 
 -0.1246930   0.5834263 
> unname(coef(mod))
[1] -0.1246927  0.5834267 -0.3465902 -0.7608882
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
 0.06360385  0.07529229  0.04741187  0.04867417 
> unname(sqrt(diag(vcov(mod))))
[1] 0.04741187 0.04867418 0.06360385 0.07529229
> 
> proc.time()
   user  system elapsed 
   2.07    0.20    2.25