Updates to R Markdown notebooks (#189)

* urca package dependency

* Instructions to install fable.prophet

* add urca as requirement

* add urca to all rmds

Co-authored-by: Hong Ooi <hongooi@microsoft.com>
Former-commit-id: 5ca9eeb7b1

R_utils/cluster.R

@@ -7,7 +7,7 @@
 #' @param libs The packages to load on each node, as a character vector.
 #' @param useXDR For most platforms, this can be left at its default `FALSE` value.
 #' @return
-#' A cluster object. 
+#' A cluster object.
 make_cluster <- function(ncores=NULL, libs=character(0), useXDR=FALSE)
 {
     if(is.null(ncores))

examples/grocery_sales/R/02_basic_models.Rmd

@@ -12,6 +12,7 @@ library(dplyr)
 library(tsibble)
 library(feasts)
 library(fable)
+library(urca)
 ```
 
 We fit some simple models to the orange juice data for illustrative purposes. Here, each model is actually a _group_ of models, one for each combination of store and brand. This is the standard approach taken in statistical forecasting, and is supported out-of-the-box by the tidyverts framework.

examples/grocery_sales/R/02a_reg_models.Rmd

@@ -12,6 +12,7 @@ library(dplyr)
 library(tsibble)
 library(feasts)
 library(fable)
+library(urca)
 ```
 
 This notebook builds on the output from "Basic models" by including regressor variables in the ARIMA model(s). We fit the following model types:

examples/grocery_sales/R/02b_prophet_models.Rmd

@@ -12,8 +12,13 @@ library(dplyr)
 library(tsibble)
 library(feasts)
 library(fable)
+library(urca)
 library(prophet)
+## NOTE: the following package can be installed from GitHub with
+## remotes::install_github("mitchelloharawild/fable.prophet")
 library(fable.prophet)
+
+### NOTE: You must run the 02a_reg_models.Rmd notebook before this one
 ```
 
 This notebook builds a forecasting model using the [Prophet](https://facebook.github.io/prophet/) algorithm. Prophet is a time series model developed by Facebook that is designed to be simple for non-experts to use, yet flexible and powerful.

examples/grocery_sales/R/README.md

@@ -21,6 +21,7 @@ The following packages are needed to run the basic analysis notebooks in this di
 - fable
 - feasts
 - yaml
+- urca
 - here
 
 It's likely that you will already have many of these (particularly the [Tidyverse](https://tidyverse.org) packages) installed, if you use R for data science tasks. The main exceptions are the packages in the [Tidyverts](https://tidyverts.org) family, which is a modern framework for time series analysis building on the Tidyverse.
@@ -29,7 +30,7 @@ It's likely that you will already have many of these (particularly the [Tidyvers
 install.packages("tidyverse") # installs all tidyverse packages
 install.packages("rmarkdown")
 install.packages("here")
-install.packages(c("tsibble", "fable", "feasts"))
+install.packages(c("tsibble", "fable", "feasts", "urca"))
 ```
 
 The following packages are needed to run the Prophet analysis notebook: