title: Error: argument "x" is missing, with no default
body: <p>I am getting an error: argument "x" is missing, with no default
  Upon debugging, I found this out to be in the line :
  <strong><code>MyData1&lt;- MyData()[,c(col(),col()+1)]</code></strong>
  I have tried to pass the argument as a single vector like 
  <strong><code>MyData1&lt;- MyData()[,p=c(col(),col()+1)]</code></strong></p>
  
  <blockquote>
    <p>Error: Error in [.data.frame: unused argument (p = c(col(), col() +
    1))</p>
  </blockquote>
  
  <p>This is just a snippet from my actual code:</p>
  
  <pre><code>TotalTS&lt;-ts(MyData()[,Col()],start=Start(),frequency = Fre())
      InsampleTs&lt;-window(TotalTS,start = c(Start(),1),end=c(2017,5))
      TotalTS1&lt;-ts(MyData()[,Col()+1],start=Start(),frequency = Fre())
      InsampleTs1&lt;-window(TotalTS1,start = c(Start(),1),end=c(2017,5))
  
      MyData1&lt;- MyData()[,c(col(),col()+1)]
      MyData1$util1&lt;-MyData1[,1]*100/MyData1[,2]
      popj&lt;-nrow(MyData())-length(InsampleTs)
  
  
      if(input$F6==1){
        if(input$AM==1){
  
          forecast32&lt;-hw(InsampleTs,h=Col1(),level = input$CI2)
          forecast32_1&lt;-hw(InsampleTs,h=Col1(),level = input$CI2)
  
          c&lt;-as.matrix(forecast32$x)
          d&lt;-as.matrix(forecast32_1$x)
  
          c1&lt;-as.matrix(forecast32$fitted)
          d1&lt;-as.matrix(forecast32_1$fitted)
          util2&lt;-(c1*100)/d1
          util1&lt;-(c*100)/d
          c11 &lt;- as.matrix(forecast32$mean[1:popj])
          d11&lt;- as.matrix(forecast32_1$mean[1:popj])
          c12 &lt;- as.matrix(forecast32$lower[1:popj])
          d12&lt;- as.matrix(forecast32_1$lower[1:popj])
          c13 &lt;- as.matrix(forecast32$upper[1:popj])
          d13&lt;- as.matrix(forecast32_1$upper[1:popj])
  
          c111 &lt;- c11*100/d11
        c112&lt;- c12*100/d12
          c113 &lt;- c13*100/d13
          MyData1$util2 &lt;- util2
          MyData1 &lt;- MyData1[,c(col(),col()+1)]
  
          e&lt;-as.matrix(forecast32$mean[-c(1:popj)])
          f&lt;-as.matrix(forecast32_1$mean[-c(1:popj)])
          e2&lt;-as.matrix(forecast32$upper[-c(1:popj)])
          f2&lt;-as.matrix(forecast32_1$upper[-c(1:popj)])
          e1&lt;-as.matrix(forecast32$lower[-c(1:popj)])
          f1&lt;-as.matrix(forecast32_1$lower[-c(1:popj)])
  
          e111 &lt;- e*100/f
          e113&lt;- e2*100/f2
          e112 &lt;- e1*100/f1
  
         r&lt;- cbind(e111,e112,e113)
         colnames(r) &lt;- c("Predicted","lower Limit","Upper Limit")
  
          MyData1 &lt;- ts(MyData1,start=c(Start(),1), end=c(2017,5), frequency=Fre())
          #r&lt;-ts(r,start=c(2017,6),end=c((Hstar()+2),Fre()))
          r&lt;-ts(r,start=c(2017,6),end=c(2019,6), frequency = 12)
          autoplot(ts( cbind(r,MyData1),start = c(Start(),1),frequency=Fre() ),facets = F)
          }**strong text**
  </code></pre>