R Under development (unstable) (2024-06-25 r86831 ucrt) -- "Unsuffered Consequences"
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> library(deming)
> 
> # Data set from Sen.  Since it is monotone the Thiel-Sen and PB regressions
> #  are identical
> #
> sen <- data.frame(t=c(1,  2,  3,  4, 10, 12, 18),
+                   y=c(9, 15, 19, 20, 45, 55, 78))
> fit <- pbreg(y ~ t, data=sen, conf=.93)
> all.equal(coef(fit), c("(Intercept)"=6, "t"=4))
[1] TRUE
> all.equal(fit$ci[2,], c(26/7, 35/8), check.attributes=FALSE)
[1] TRUE
> 
> fit2 <- pbreg(y ~ t, data=sen, conf=.93, method=2)
> fit3 <- pbreg(y ~ t, data=sen, conf=.93, method=3)
> all.equal(coef(fit2), coef(fit))
[1] TRUE
> all.equal(coef(fit3), coef(fit))
[1] TRUE
> all.equal(fit2$ci, fit$ci)
[1] TRUE
> all.equal(fit3$ci, fit$ci)
[1] TRUE
> 
> # Simple data set with noise
> pdata <- data.frame(x=1:6, y=c(2,1.2, 4.1,3.5,6.3, 3))
> fit <- pbreg(y~x, pdata)
> all.equal(coef(fit), c(1/8, 1.05), check.attributes=FALSE)
[1] TRUE
> 
> fit3 <- pbreg(y ~ x, pdata, method=3)
> all.equal(coef(fit3), coef(fit))
[1] TRUE
> 
> fit2 <- pbreg(y ~ x, pdata, method=2)
> temp <- tan(mean(c(atan(2.2/2), atan(4.3/4))))
> all.equal(as.vector(coef(fit2)), c(median(pdata$y- pdata$x*temp), temp))
[1] "Mean relative difference: 0.05024691"
> 
> # test case with boot library
> # library(boot)
> # bfit <- pbreg(aes ~ aas, arsenate, method=3, nboot=500)
> 
> proc.time()
   user  system elapsed 
   0.21    0.06    0.26