works now with most time series classes, as supported by the tsbox package.
disagregation is possible to all frequencies (e.g., monthly to daily).
Disaggregation takes into account the calendar, e.g., the fact that February
is shorter than other months. (#30)
new method: "fast", a shortcut for chow-lin-fixed with fixed.rho = 0.99999.
The method returns approximately the same results as "denton-cholette", but is
much faster. (#14)
new vignettes: intro to tempdisagg, disaggregation to high frequency
new methods: "dynamic-maxlog", "dynamic-minrss", "dynamic-fixed", as described in
Santos Silva and Cardoso, 2001. Many thanks to Tommaso Di Fonzo for providing
a blueprint written in GAUSS.
retropolation: 'td' will performs both extra- and retropolation if the high
frequency series covers a larger time span than the low frequency series.
low frequency values are ignored if series is longer than high frequency
series (with a warning).
suggestion to use 'denton-cholette' when the original 'denton' method is
chosen.
tempdisagg 0.23 (2014-01-11)
changes visible to the user
Our R-Journal article on temporal disaggregation explains tempdisagg in more
detail. Links are included in the package description, the help files and
the README file.
minor changes
warning in ta() if a time series contains internal NAs.
formating tweaks in the help files.
tempdisagg 0.22 (2013-08-07)
changes visible to the user
predict method for 'td' is now different from fitted:
$fitted.values of a 'td' object now containts the low-frequency fitted
values of a regression or the low-frequency indicator in case of the
Denton methods. The values are be accessed by fitted().
The final high frequency series is now stored in $values. As before, these
values are accessed by predict().
Package overview (?tempdisagg)
Demo (demo(tempdisagg))
argument 'truncated.rho = 0' instead of 'no.neg = TRUE'. This allows for
truncation values different from 0. Default behavior is the same as in 0.21.
bug fixes
in 0.21, ta() produced an error if less than a low-frequency unit was
covered by high frequency data. Now it produces series containing only NA.
If a singular data matrix is entered, there is a new warning.
tempdisagg 0.21 (2013-01-21)
changes visible to the user
new methods available: "chow-lin-fixed" and "litterman-fixed".
Using the "fixed.rho" argument, an autoregressive parameter may be specified
by the user.
interface changes: "chow-lin-maxlog-ecotrim" and "chow-lin-maxlog-quilis"
are defined as new methods. No need for the old 'vcov' argument anymore.
new defaults: method = "chow-lin-maxlog", neg.rho = FALSE
with positive values for rho only, the chow-lin-maxlog method generally
outperforms the other methods.
all relevant arguments are directly entered to td()
summary output: If neg.rho = FALSE and a negative rho is truncated to 0, and
indicator is shown in the summary output.
non time-series mode: optionally, standard vectors can be used instead of
time series. In this case, the frequency of low frequency variable is 1,
while the fraction of the high frequency variable is specified by the 'to'
argument
updated help files
under the hood
td() is rewritten and has a clear structure now.
GLS Regressions are performed by the new CalcGLS() function, which uses
QR-decomposition instead of matrix-inversion. This is faster and
numerically stable. It resolves an issue wher large (or small) numbers have
led to a 'system is computationally singular' error.