 Having trouble showing dates on the x-axis (using plot.forecast) of a
weekly time series (forecast object produced by forecast) instead of
numbers. (The x-axis labels of the attached chart range from 0 to 300
instead of dates.) I notice the print function doesn't show dates as well.
Is it because I am converting a timeSeries object to a ts object? Is it due
to the weekly periodicity?

Hope this isn't too basic a question!

Thanks for your help in Advance.

John E. Kaprich, CFA

> library(timeSeries)
> library(forecast)
>
> DataFVM <- read.table("Data Forecast (FVM).txt", header=TRUE, sep="\t",
colClasses = c("character", "numeric",
"numeric","numeric","numeric","numeric","numeric","numeric"))
>
> DataFVMTs <- timeSeries (DataFVM[-1], DataFVM[[1]], format = "%Y/%m/%d")
> as.ts (DataFVMTs)
> is.timeSeries (DataFVMTs)
TRUE
>
> head(DataFVMTs)

GMT
           X10yrInflationSwap MOVE.Index Initial.Jobless.Claims
USSOC.CURNCY SPX.Earn.Yld
2009-06-26              94.04      159.0                 598.25
0.216       6.2203
2009-07-03              93.98      149.1                 592.50
0.201       5.9356
2009-07-10              92.82      135.9                 580.25
0.194       6.0565
2009-07-17              95.36      156.3                 568.25
0.191       5.6613
2009-07-24              94.82      143.6                 566.50
0.196       5.4343
2009-07-31              94.47      138.5                 562.00
0.201       5.3887
           Global.Sovereogn.Spread Quality.Spread
2009-06-26                 469.605           1.77
2009-07-03                 442.265           1.78
2009-07-10                 458.125           1.76
2009-07-17                 415.269           1.75
2009-07-24                 398.715           1.67
2009-07-31                 402.360           1.51

 > MOVE <- tbats(DataFVMTs[,2])

> fcMOVE <- forecast(MOVE, h=24)

> print(fcMOVE)

 Point Forecast    Lo 80    Hi 80    Lo 95    Hi 95
266       55.14267 49.81179 61.04407 47.20169 64.41961
267       54.72591 47.78525 62.67467 44.47486 67.33973
268       55.34932 47.17508 64.93995 43.34857 70.67240
269       55.92950 46.78320 66.86394 42.56346 73.49284
270       56.46898 46.52149 68.54349 41.98595 75.94792
271       56.97021 46.34421 70.03259 41.54669 78.11946
272       57.43557 46.22430 71.36601 41.20457 80.06015
273       57.86732 46.14446 72.56835 40.93317 81.80718
274       58.26766 46.09299 73.65807 40.71449 83.38849
275       58.63865 46.06170 74.64969 40.53581 84.82602
276       58.98227 46.04471 75.55500 40.38783 86.13752
277       59.30037 46.03770 76.38379 40.26363 87.33774
278       59.59473 46.03749 77.14435 40.15794 88.43910
279       59.86700 46.04167 77.84380 40.06672 89.45225
280       60.11875 46.04845 78.48830 39.98682 90.38640
281       60.35144 46.05648 79.08326 39.91578 91.24955
282       60.56645 46.06476 79.63344 39.85165 92.04875
283       60.76506 46.07252 80.14305 39.79290 92.79022
284       60.94847 46.07922 80.61585 39.73831 93.47946
285       61.11780 46.08447 81.05519 39.68690 94.12138
286       61.27410 46.08798 81.46409 39.63789 94.72036
287       61.41834 46.08958 81.84525 39.59069 95.28032
288       61.55143 46.08915 82.20110 39.54478 95.80477
289       61.67420 46.08663 82.53385 39.49979 96.29689

 > plot.forecast(fcMOVE)

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