[R] using forecast() in dse2 with an ARMA model having a trend component

[Paul Gilbert]

Scott

This works for me:

 > arma.pred.without.trend$forecast[[1]][,1]
 [1] 106.0038 105.9789 105.9605 105.9396 105.9224 105.9052 105.8926 105.8849
 [9] 105.8812 105.8880 105.9043 105.9240 105.9579 105.9878 105.9901 106.0095
[17] 106.0555 106.0782 106.0644 106.0427 106.0297 106.0072 106.0126 106.0125
 > arma.pred.with.trend$forecast[[1]][,1]
 [1] 101.49566  97.46626  93.89069  90.70991  87.88602  85.37563  83.14843
 [8]  81.17338  79.42193  77.87562  76.51150  75.30371  74.24589  73.30438
[15]  72.44303  71.69453  71.05658  70.47036  69.91559  69.41396  68.97527
[22]  68.57536  68.24555  67.94755

There was a bug that may be related to this fixed in the version 
dse_2005.4-1, which has been on CRAN for a month or so.  The above 
result was actually with my working copy, but I don't recall any more 
recent changes that would affect this.  If you actually have the 
2005.4-1 version and are still having this problem then please let me 
know and I will check more carefully.  (In that case, OS details would 
be helpful too.)

Paul Gilbert

Waichler, Scott R wrote:

>(My apologies if this is a repeated posting.  I couldn't find any trace
>of my previous attempt in the archive.)  
>
>I'm having trouble with forecast() in the dse2 package.  It works fine
>for me on a model without a trend, but gives me NaN output for the
>forecast values when using a model with a trend.  An example:
>
># Set inputs and outputs for the ARMA model fit and test periods
>arma.fit.input <- c(105.3332, 105.3573, 105.3113, 105.1493, 105.1209,
>105.2111, 104.9161,
>                    105.3654, 105.4682, 105.6789, 105.6297, 106.0155,
>105.8454, 105.4322,
>                    105.6062, 106.0739, 106.1109, 105.4470, 104.9739,
>105.3427, 105.4305,
>                    105.2563, 104.8501, 105.0358, 105.2827, 104.8977)
>
>arma.fit.output <- c(106.0376, 106.0514, 106.0716, 106.0570, 106.0442,
>106.0414, 106.0375,
>                     106.0169, 106.0268, 106.0670, 106.1169, 106.1544,
>106.1898, 106.2252,
>                     106.2605, 106.2959, 106.3324, 106.3974, 106.3460,
>106.2357, 106.1897,
>                     106.1811, 106.1556, 106.1130, 106.0805, 106.0791)
>
>arma.pred.input <- c(104.9916, 104.8207, 104.8936, 104.8767, 104.9435,
>104.8885, 104.9217,
>                     104.9029, 104.9508, 105.0065, 105.0557, 105.1982,
>105.3392, 105.4007,
>                     105.6212, 105.5979, 105.2410, 105.4832, 105.8735,
>105.5944, 105.1063,
>                     104.9809, 105.0821, 104.9362, 105.3037, 105.2322)
>arma.pred.output <- c(106.0528, 106.0293, 106.0053, 105.9850, 105.9697,
>105.9604, 105.9509,
>                      105.9430, 105.9357, 105.9314, 105.9333, 105.9420,
>105.9640, 105.9994,
>                      106.0290, 106.0855, 106.1265, 106.1197, 106.1245,
>106.1893, 106.2118,
>                      106.1503, 106.0883, 106.0511, 106.0194, 106.0221)
>
># Set TSdata object
>arma.fit.TSdata <- TSdata(input = arma.fit.input, output =
>arma.fit.output)
>
># Fit the model
>arma.model.without.trend <- estVARXls(arma.fit.TSdata, max.lag=1,
>trend=F)
>arma.model.with.trend    <- estVARXls(arma.fit.TSdata, max.lag=1,
>trend=T)
>
># Apply the model for the test period
>arma.pred.TSdata <- TSdata(input = arma.pred.input, output =
>arma.pred.output[1:2]) arma.pred.without.trend <-
>forecast(TSmodel(arma.model.without.trend), arma.pred.TSdata)
>arma.pred.with.trend    <- forecast(TSmodel(arma.model.with.trend),
>arma.pred.TSdata)
>
>The results:
>  
>
>>arma.pred.without.trend$forecast[[1]][,1]
>>    
>>
> [1] 106.0038 105.9789 105.9605 105.9396 105.9224 105.9052 105.8926
>105.8849  [9] 105.8812 105.8880 105.9043 105.9240 105.9579 105.9878
>105.9901 106.0095 [17] 106.0555 106.0782 106.0644 106.0427 106.0297
>106.0072 106.0126 106.0125
>  
>
>>arma.pred.with.trend$forecast[[1]][,1]
>>    
>>
> [1] 5.76056e+228          NaN          NaN          NaN          NaN
> [6]          NaN          NaN          NaN          NaN          NaN
>[11]          NaN          NaN          NaN          NaN          NaN
>[16]          NaN          NaN          NaN          NaN          NaN
>[21]          NaN          NaN          NaN          NaN
>
>I read help on this function and the PDF manuals but can't see what I
>might be missing.  
>Any ideas?  
>
>Thanks, Sott Waichler
>Pacific Northwest National Laboratory
>scott.waichler at pnl.gov
>
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