Description Usage Arguments Details Value Author(s) See Also
View source: R/disaggregate.MARN.R
For a brief introduction on disaggregation see
disaggregate.ts
.
In order to disaggregate, a distribution of the
asterisks is required. In this
implementation, the distribution is estimated
using a surrogate serie. In
general terms the surrogate serie is very
carefully drafted.
1 2 3 | disaggregate.MARN(stream = NULL, reference = NULL,
na.action = "error", asterisk = -9999, date.eps = 0.004,
float.eps = 1e-04, return.incomplete = TRUE)
|
stream |
An aggregated |
reference |
A reference or surrogate |
na.action |
Action to take if the sample distribution has NAs present.
Can be |
asterisk |
Scalar denoting values to complete. |
date.eps |
Tolerance in date/time matching. |
float.eps |
Smallest mass to distribute along the aggregated elements. |
return.incomplete |
Boolean value to interrupt the process and return the incompletely disaggregated series. See details. |
The parametre return.incomplete is very usefull to build surrogate series, as follows. Say there is a list of 15 aggregated series, then in order to build a reference series for all of them, the following hueristic can help. Suppose these series are ordered by least NAs and asterisks present.
1 2 3 4 5 6 7 8 9 |
The main feature of this procedure is that it always tries to use the best serie first then the second best, etc. It may not complete the task if the sample distribution contains NAs for all 15 stations. Under this precarious condition, artificial or external information can be used.
Returns a disaggregated series. If the switch return.incomplete is true, then it returns a series that was disaggregated until NAs where found on the sample distribution.
A.M. Sajo-Castelli
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