speed-up fix

This passes only necessary variables to ddply, which considerably speeds up the function on large data frames. Here are some tests on a [training set](http://www.qog.pol.gu.se/) of 14,137 rows and 728 variables.

    > dim(QOG)
    [1] 14137   731
    > # lag test
    > system.time(QOG$oil_lag2 <- lagpanel(QOG$ross_oil_price, QOG$ccode, QOG$year, 2))
       user  system elapsed 
      0.220   0.010   0.231 
    > system.time(QOG <- slide(QOG, "ross_oil_price", "ccode", "oil_lag2", slideBy = -2))
       user  system elapsed 
     20.783   3.359  24.299 
    > system.time(QOG <- slide2(QOG, "ross_oil_price", "ccode", "oil_lag2", slideBy = -2))
       user  system elapsed 
      0.189   0.016   0.207 
    > 
    > # lead test
    > system.time(QOG <- slide(QOG, "wdi_gdpc", "ccode", "oil_lead5", slideBy = 5))
       user  system elapsed 
     20.265   3.458  23.768 
    > system.time(QOG <- slide2(QOG, "wdi_gdpc", "ccode", "oil_lead5", slideBy = 5))
       user  system elapsed 
      0.187   0.014   0.201