Add custom packages to Azure Machine Learing Studio

Question

I need to use the function tsCV on azure machine learning studio to evaluate models of forecast, but i got the error

could not find function "tsCV

I'm trying to update the forecast package, but no package are loaded. I followed this tutorial http://blog.revolutionanalytics.com/2015/10/using-minicran-in-azure-ml.html and https://blog.tallan.com/2016/12/27/adding-r-packages-in-azure-ml/ but i dont get the same result. No packages are load.

I need an example of a package with R code that works o Azure ML or an update of forecast package to use tsCV function.

Answer 1

I have installed the latest version of the forecast package and here are the steps I followed during the installation.

1. Download latest version of CRAN
2. Be sure that tsCV is working locally
3. Zip all the dependencies + forecast package
4. Zip all the generated zips together and upload it to the AMLStudio
5. Run the following code:

install.packages("src/glue.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/stringi.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/assertthat.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/fansi.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/utf8.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/stringr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/labeling.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/munsell.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/R6.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/RColorBrewer.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/cli.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/crayon.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/pillar.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/xts.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/TTR.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/curl.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/digest.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/gtable.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/lazyeval.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/plyr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/reshape2.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/rlang.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/scales.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/tibble.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/viridisLite.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/withr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/quadprog.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/quantmod.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/colorspace.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/fracdiff.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/ggplot2.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/lmtest.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/magrittr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/Rcpp.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/timeDate.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/tseries.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/urca.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/uroot.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/zoo.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/RcppArmadillo.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/forecast.zip", lib = ".", repos = NULL, verbose = TRUE)

library(forecast, lib.loc=".", verbose=TRUE)
far2 <- function(x, h){forecast(Arima(x, order=c(2,0,0)), h=h)}
e <- tsCV(lynx, far2, h=1)

Here is the zip I have generated: