Running R3.3.2 and Knime 3.3
In RStudio, I am able to demonstrate the following behavior:
1) Seasonal Sales through auto.arima chooses model (1,0,1)(0,1,0)[12]
2) Same data after Multiplicative Seasonality ajustment fed into auto.arima then chooses model (0,1,0) only.
This was expected in RStudio.
So, when I attempt the same script in R Snippet using BOTH data files for knime.in both data streams evaluate to (0,1,0) which is expected for the Adjusted Sales (ts_binders2.csv), but not for the Raw Sales (ts_binders.csv).
Anyone have an idea about why the script would evaluate differently in Knime R Snippet than it does in R Studio?
FYI, I've attached RStudio screen shots and exported Knime test workflow and the 2 data files producing different results in RStudio vs. R Snippet in Knime.
Thanks. Jeff
Script:
library(forecast)
sales <- knime.in$"ORIG_SALES_AMT (formatted)"
salests <- ts(sales, frequency=12, start=c(2013,1))
mod <- auto.arima(salests)
xp <- toString(arimaorder(mod)[1])
xd <- toString(arimaorder(mod)[2])
xq <- toString(arimaorder(mod)[3])
xP <- toString(arimaorder(mod)[4])
xD <- toString(arimaorder(mod)[5])
xQ <- toString(arimaorder(mod)[6])
xperd <- toString(arimaorder(mod)[7])
xdf <- data.frame(vp = character(),
vd = character(),
vq = character(),
vP = character(),
vD = character(),
vQ = character(),
vperd = character())
xrow <- data.frame(vp=xp, vd=xd, vq=xq,
vP=xP, vD=xD, vQ=xQ,
vperd=xperd)
xdf <- rbind(xdf, xrow)
knime.out <- xdf
Any