Alegerea dimensiunii setului de calibrare în predicție conformă cu ahead::conformalize()

În versiunea 0.39.0 a ahead pachet, cel conformalize() funcția a fost actualizată pentru a include un nou parametru numit split_prob. Acest parametru permite utilizatorilor să specifice proporția de date care ar trebui utilizată pentru calibrare atunci când se construiesc intervale de predicție conforme.

install.packages("pak")

pak::pak("Techtonique/ahead")

library(ahead)

par(mfrow=c(2, 2))
obj <- ahead::conformalize(FUN = forecast::ets, y = USAccDeaths,
                           h = 20L, split_prob = 0.4)
plot(obj)
obj <- ahead::conformalize(FUN = forecast::ets, y = USAccDeaths,
                           h = 20L, split_prob = 0.3)
plot(obj)
obj <- ahead::conformalize(FUN = forecast::ets, y = USAccDeaths,
                           h = 20L, split_prob = 0.6)
plot(obj)
obj <- ahead::conformalize(FUN = forecast::ets, y = USAccDeaths,
                           h = 20L, split_prob = 0.7)
plot(obj)

par(mfrow=c(2, 2))
obj <- ahead::conformalize(FUN = forecast::ets, y = AirPassengers,
                           h = 20L, split_prob = 0.4)
plot(obj)
obj <- ahead::conformalize(FUN = forecast::ets, y = AirPassengers,
                           h = 20L, split_prob = 0.3)
plot(obj)
obj <- ahead::conformalize(FUN = forecast::ets, y = AirPassengers,
                           h = 20L, split_prob = 0.6)
plot(obj)
obj <- ahead::conformalize(FUN = forecast::ets, y = AirPassengers,
                           h = 20L, split_prob = 0.7)
plot(obj)

par(mfrow=c(2, 2))
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = fdeaths,
                           h = 20L, split_prob = 0.4)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = fdeaths,
                           h = 20L, split_prob = 0.3)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = fdeaths,
                           h = 20L, split_prob = 0.6)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = fdeaths,
                           h = 20L, split_prob = 0.7)
plot(obj)

par(mfrow=c(2, 2))
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = UKDriverDeaths,
                           h = 20L, split_prob = 0.4)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = UKDriverDeaths,
                           h = 20L, split_prob = 0.3)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = UKDriverDeaths,
                           h = 20L, split_prob = 0.6)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = UKDriverDeaths,
                           h = 20L, split_prob = 0.7)
plot(obj)

par(mfrow=c(2, 2))
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = WWWusage,
                           h = 20L, split_prob = 0.4)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = WWWusage,
                           h = 20L, split_prob = 0.3)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = WWWusage,
                           h = 20L, split_prob = 0.6)
plot(obj)
obj <- ahead::conformalize(FUN = ahead::dynrmf, y = WWWusage,
                           h = 20L, split_prob = 0.5)
plot(obj)