library(blblm)
fit <- blblm(mpg ~ wt * hp, data = mtcars, m = 3, B = 100)
coef(fit)
#> (Intercept) wt hp wt:hp
#> 48.88428523 -7.88702986 -0.11576659 0.02600976
confint(fit, c("wt", "hp"))
#> 2.5% 97.5%
#> wt -10.7902240 -5.61586271
#> hp -0.1960903 -0.07049867
sigma(fit)
#> [1] 1.838911
sigma(fit, confidence = TRUE)
#> sigma lwr upr
#> 1.838911 1.350269 2.276347
predict(fit, data.frame(wt = c(2.5, 3), hp = c(150, 170)))
#> 1 2
#> 21.55538 18.80785
predict(fit, data.frame(wt = c(2.5, 3), hp = c(150, 170)), confidence = TRUE)
#> fit lwr upr
#> 1 21.55538 20.02457 22.48764
#> 2 18.80785 17.50654 19.71772