forecasting ARIMA model with extra regressors
<p>Suppose i have some time series as below and i want to forecast <code>c1</code> one step a head, doing so is pretty straight forward and easy in R: </p>

<pre><code>testurl = "https://docs.google.com/spreadsheets/d/1jtpQaSxNY1V3b-Xfa5OJKDCLE6pNlzTbwhSHByei4EA/pub?gid=0&amp;single=true&amp;output=csv"
test = getURL(testurl)
mydata = read.csv(textConnection(test), header = TRUE)
data &lt;- ts(mydata['c1'])
fit &lt;- auto.arima(data)
fcast &lt;- forecast(fit)
fcast
</code></pre>

<p>note that the numbers is just random numbers, and the auto.arima suggest us to use an <code>arima(0,1,0)</code> and the forecast one step a head is 52. </p>

<p>however, what if one want to use <code>c2</code> and <code>c3</code> to improve (in terms of aic and bic for example) the out of sample forecast? how would one actually continue then? </p>

<pre><code>c1   c2     c3
40   0,012  1
41   0,015  1
42   0,025  1
40  −0,015  1
44   0,000  0
50   0,015  0
52   0,015  1
51   0,020  1
50   0,025  1
52   0,030  0
53   0,045  1
52   0,030  1
52   0,025  0
52   0,000  0
51   0,010  0
50  −0,02   1
48  −0,025  1
49  −0,030  1
51  −0,040  1
52  −0,350  0
</code></pre>