Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(ForecastTB)
## -----------------------------------------------------------------------------
a <- prediction_errors(data = nottem) #`nottem` is a sample dataset in CRAN
a
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
b <- plot(a)
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
library(decomposedPSF)
test1 <- function(data, nval){
return(lpsf(data = data, n.ahead = nval))
}
library(PSF)
test2 <- function(data, nval){
a <- psf(data = data, cycle = 12)
b <- predict(object = a, n.ahead = nval)
return(b)
}
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
a1 <- prediction_errors(data = nottem, nval = 48,
Method = c("test1(data, nval)", "test2(data, nval)"),
MethodName = c("LPSF","PSF"), append_ = 1)
a1@output$Error_Parameters
b1 <- plot(a1)
## ----fig.height = 8, fig.width = 8, fig.align = "center"----------------------
library(forecast)
test3 <- function(data, nval){
b <- as.numeric(forecast(ets(data), h = nval)$mean)
return(b)
}
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
c1 <- append_(object = a1, Method = c("test3(data,nval)"), MethodName = c('ETS'))
c1@output$Error_Parameters
d1 <- plot(c1)
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
pcv <- function(obs, pred){
d <- (var(obs) - var(pred)) * 100/ var(obs)
d <- abs(as.numeric(d))
return(d)
}
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
a1 <- prediction_errors(data = nottem, nval = 48,
Method = c("test1(data, nval)", "test2(data, nval)"),
MethodName = c("LPSF","PSF"),
ePara = "pcv(obs, pred)", ePara_name = 'PCV',
append_ = 1)
a1@output$Error_Parameters
b1 <- plot(a1)
## ----fig.height = 6, fig.width = 8, fig.align = "left"------------------------
plot_circle(a1)
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
a1 <- prediction_errors(data = nottem, nval = 48,
Method = c("test1(data, nval)"),
MethodName = c("LPSF"), append_ = 1)
monte_carlo(object = a1, size = 180, iteration = 10)
## ----fig.height = 7, fig.width = 7, fig.align = "center"----------------------
monte_carlo(object = a1, size = 144, iteration = 2, fval = 1, figs = 1)
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