This question is about generate_msts() function in package GRATIS.
I add some new stuff (make the function has options to transform its output into a lovely tsibble format or keep the original ‘list’ format) and prepare update to CRAN.
New code add as below (detail of the codes with example shown at the bottom of the question)
I wonder should I get tsibble a index? But the generated data seems like do not have a index?
output <- if (output_format == "list") {
res #this is output name defined before
} else if (output_format == "tsibble") {
as_tsibble(res)
}
return(output)
}
And as a guidance, I update the corresponding example for this function in Vignette. Then things become wired.
If I did not save the generated time series output (e.g. x <- my_function()), the vignette cannot knit out. (However, I can use this function directly in an independent normal RMD file)
Use this code directly can show output inside RStudio, but cannot be knit out.
my_function(seasonal.periods = c(7, 365), n = 800, nComp = 2,output_format="tsibble")
Error in Fun(X[[i]],...): 'list' object cannot be coerced to type 'integer' Calls: <Anonymous>...
as.data.frame -> head -> head.data.frame -> lappy -> FUN Execution halted.
But, this works fine. It can knit out the vignette and shows head of tsibble.
x <- my_function(seasonal.periods = c(7, 365), n = 800, nComp = 2,output_format="tsibble")
head(x)
However, this is very inconvenience to save it each time before you can use it. I wonder if this is because there is any default setting I used in package or vignette does not change? Or there is some extra step I need to do after I change the function inside R package? Or even the if else content I add need to be improved?
I have tried devtools::document("C:/Users/mreal/Documents/GitHub/package_name");devtools::install("C:/Users/mreal/Documents/GitHub/package_name") to update the re-build function. But this still does not help vignette.
I also tried rm(list=ls()) in console. It does not work as well
Code I used in vignette is as below
Github link:
https://github.com/BocongZhao823/gratis/blob/master/vignettes/QuickStart.Rmd
---
title: "Introduction to gratis"
author: "Bocong Zhao"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Introduction to gratis}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
{r initial, echo = FALSE, cache = FALSE, results = 'hide'}
library(knitr)
opts_chunk$set(
warning = FALSE, message = FALSE, echo = TRUE,
fig.width = 7, fig.height = 6, fig.align = 'centre',
comment = "#>"
)
original <- options("tibble.print_min")
options(tibble.print_min = 5)
# <---- Do stuff with changed option, e.g. print some tibbles ---->
options(tibble.print_min = original)
{r, message=FALSE, include = FALSE}
library(forecast)
library(tsibble)
{r setup}
# load package
library(gratis)
## Generate mutiple seasonal time series
Time series can exhibit multiple seasonal pattern of different length, especially when series observed at a high frequency such as daily or hourly data.
We use function **generate_msts()** to generate mutiple seasonal time series.
**Definitions**
Here are the definitions of parameter settings in function generate_msts():
|parameter settings | Definition|
|:----|:-----|
|seasonal.periods | a vector of seasonal periods of the time series to be generated|
|nComp|number of mixing components when simulating time series using MAR models|
|n |length of the generated time series|
**Example**
Suppose we want to use MAR model to generate a time series with **2** mixing components and the length **800** from random parameter spaces. Particularly, this time series has two seasonal periods **7** and **365**.
{r fig.height = 6, fig.width = 7}
# Generate mutiple seasonal time series with 'tsibble' output format
x <- generate_msts(seasonal.periods = c(7, 365), n = 800, nComp = 2,output_format="tsibble")
head(x)
**Plot time series**
{r fig.height = 6, fig.width = 7}
# Generate mutiple seasonal time series with 'list' output format
x <- generate_msts(seasonal.periods = c(7, 365), n = 800, nComp = 2,output_format="list")
autoplot(x)
(generated.R file) The R code used inside a package is as below
** Github link**
https://github.com/BocongZhao823/gratis/blob/master/R/generate_ts.R
#' Generate mutiple seasonal time series from random parameter spaces of the mixture autoregressive (MAR) models.
#'
#' Generate mutiple seasonal time series from random parameter spaces of the mixture autoregressive (MAR) models.
#' @param seasonal.periods a vector of seasonal periods of the time series to be generated.
#' @param n length of the generated time series.
#' @param nComp number of mixing components when simulating time series using MAR models.
#' @param output_format An optional argument which allows to choose output format between "list" and "tsibble"
#' @return a time series with multiple seasonal periods.
#' @export
#' @examples
#' x <- generate_msts(seasonal.periods = c(7, 365), n = 800, nComp = 2, output_format= "list")
#' forecast::autoplot(x)
generate_msts <- function(seasonal.periods = c(7, 365), n = 800, nComp = NULL,output_format="list") {
x.list <- map(seasonal.periods, function(p) {
generate_ts(n.ts = 1, freq = p, n = n, nComp = nComp)$N1$x
})
names(x.list) <- paste0("Season", seasonal.periods)
x.list[1:(length(x.list) - 1)] <- lapply(x.list[1:(length(x.list) - 1)], function(x) {
x - trendcycle(stl(x, "per"))
})
weights <- msts_weights(length(seasonal.periods))
res <- as_tibble(scale(x.list %>% bind_cols())[, ]) %>%
mapply("*", ., weights) %>%
as_tibble() %>%
mutate(x = rowSums(.)) %>%
select(x) %>%
msts(seasonal.periods = seasonal.periods)
# New content
output <- if (output_format == "list") {
res
} else if (output_format == "tsibble") {
as_tsibble(res)
}
return(output)
}
# ===========================================================================
# Simulated weights for the simulation of msts
# ===========================================================================
msts_weights <- function(n.periods) {
gamma <- runif(n.periods, 0)
weights <- gamma / sum(gamma)
return(weights)
}
else if( output_format == "tsibble") {res <- map(res, ~ {.x <- as_tsibble(.x$x); .x})}– Lupelupee.x$x <- as_tsibble(.x$x)– Lupelupeetibble::as_tsibbleinstead ofas_tsibble? The idea being that it might load packages weirdly, so specifying 'where' might remove confusion. – Amass