TRAMO for ERRORs (TERROR) controls the quality of the data by checking outliers at the end of the series
Usage
terror(
ts,
spec = c("trfull", "tr0", "tr1", "tr2", "tr3", "tr4", "tr5"),
nback = 1,
context = NULL
)
Value
a mts
object with 7 variables:
actual
the actual data at the end of the series.forecast
the forecast of the actual data at the end of the series.error
the absolute errors (= observed - forecasts).rel.error
relative errors ("scores") : ratios between the forecast errors and the standard deviation of the forecasts of the last observations (positive values mean under-estimation).raw
the transformed series. More especially, if the chosen model implies a log-transformation, the values are obtained after a log-transformation. Other transformations, such leap year corrections or length-of periods corrections may also be used.fraw
the forecast of the transformed series.efraw
the absolute errors of the transformed series.