R Under development (unstable) (2025-10-18 r88943 ucrt) -- "Unsuffered Consequences"
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> 
> library("MASS")
> options(digits = 4)
> 
> 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.' -1772 (df=4)
> logLik(mod)
'log Lik.' -1772 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
    0.5636     1.2487 
> mp$zeta
 Low|Medium Medium|High 
    -0.2014      0.9485 
> ### PR#17616
> unname(coef(mod))
[1] -0.2014  0.9485 -0.5636 -1.2487
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
    0.10357     0.12479     0.07663     0.08024 
> unname(sqrt(diag(vcov(mod))))
[1] 0.07663 0.08024 0.10357 0.12479
> 
> 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 (df=4)
> logLik(mod)
'log Lik.' -1776 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
    0.3851     0.7838 
> mp$zeta
 Low|Medium Medium|High 
     0.2426      1.0315 
> unname(coef(mod))
[1]  0.2426  1.0315 -0.3851 -0.7838
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
    0.07219     0.07954     0.05454     0.06091 
> unname(sqrt(diag(vcov(mod))))
[1] 0.05454 0.06091 0.07219 0.07954
> 
> 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.' -1773 (df=4)
> logLik(mod)
'log Lik.' -1773 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
    0.3663     0.8792 
> mp$zeta
 Low|Medium Medium|High 
    -0.5679      0.2655 
> unname(coef(mod))
[1] -0.5679  0.2655 -0.3663 -0.8792
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
    0.06980     0.09157     0.05441     0.04894 
> unname(sqrt(diag(vcov(mod))))
[1] 0.05441 0.04894 0.06980 0.09157
> 
> 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 (df=4)
> logLik(mod)
'log Lik.' -1772 (df=4)
> 
> coef(mp)
InflMedium   InflHigh 
    0.3466     0.7609 
> mp$zeta
 Low|Medium Medium|High 
    -0.1247      0.5834 
> unname(coef(mod))
[1] -0.1247  0.5834 -0.3466 -0.7609
> 
> sqrt(diag(vcov(mp)))

Re-fitting to get Hessian

 InflMedium    InflHigh  Low|Medium Medium|High 
    0.06360     0.07529     0.04741     0.04867 
> unname(sqrt(diag(vcov(mod))))
[1] 0.04741 0.04867 0.06360 0.07529
> 
> proc.time()
   user  system elapsed 
   1.34    0.26    1.59