disaggR 1.0.5.1

Internal change to check package version with character instead of numeric.
Internal minor change to in_disaggr (incohesive parameters)
A more informative error message if one tries to differentiate a time-series with only one observation
A more informative error message if the rank becomes imperfect after decorrelation

disaggR 1.0.5

Breaking change : The order of the output of the reViewOutput object has been reversed. reView and rePort can now take a language object as name arguments and return language objects inside their name attributes (PR #86)
The print method digit argument is now passed to everything below. The default value is getOption("digits") for the benchmarks and max(3L, getOption("digits")) for the praislm objects.

Internal change from ggplot2 size argument, which is deprecated for lines, to linewidth (PR #78)

Added the arguments hfserie_name and lfserie_name for rePort, as for reView. (PR #70)
Added a vignette describing the use of outliers. (PR #74)
reView no longer throws the message “This Font Awesome icon (‘info-circle’) does not exist”.

Added the signature c("disaggR","missing") for Ops group generic. (PR #54)
Inner calls to aggregate are now redirected to a faster non-exported function. (PR #55)
Estimation spans and outliers are now handled in preset models in rePort and reView (PR #57)
NULL labels are now removed even outside the plot margins (PR #59)
The in_scatter function now substracts the outliers contributions from the low-frequency serie before computing the in_scatter comparison. (PR #63)
The in_scatter has now an additional arguments : type (as every in_ function). For now, the only use for the type argument is to allow changes scatterplots for levels models. (PR #63)
The smoothed.part, for differencied benchmarks, has been set to a new base (its aggregated value is 0 in 2000). That way, reUseBenchmark is fixed if used on high-frequency series that have a different start than the previous one. This has no impact on the benchmarked serie. (PR #65)

New vignette : Introduction to disaggR.
The error of in_disaggR for wrong type arguments has been changed, because it didn’t include “contributions”.
cex.axis, xlim, ylim, cex.lab and cex.main parameters now overwrite their default if used inside plot(...) dots.
By default, in the plot and autoplot methods, the axis annotations are now automatically set to be smaller if needed.

Switched ggplot2, rmarkdown and shiny from imports to suggests. RColorBrewer has replaced scales as an import. disaggR can now be installed with far less dependencies. Hence, the autoplot generic is not reexported anymore. ggplot2 has to be attached to allow the use of autoplot without the ggplot2:: prefix, by example with library(ggplot2).

added support of outliers.
In twoStepsBenchmark, the set.coeff names used to be replaced by "hfserie" if NCOL(hfserie) == 1L and length(set.coeff) == 1L. This behavior was contradictory with the documentation if set.coeff=c(constant=1L). As for now, set.coeff names will never be replaced. Then, it makes the controls stricter because set.coeff=c(x.name.herited.from.anywhere=1) will lead to an error.
as for the in time-series plots, the y window now ignores the infinite values.

reView : a shiny reviewing application for twoStepsBenchmarks.
rePort : a rmarkdown html report for twoStepsBenchmark and reView outputs.
start.domain and end.domain know crops the hfserie after having calculated the coefficients. That way, it is possible to evaluate the coefficients on a full hfserie, cropping them for the application.
in_sample now generates a more general class "tscomparison", with a "in_sample" func attribute. In previous versions, the S3 class was named “insample”.
the new functions in_scatter, in_benchmark and in_revisions also produce tscomparisons, with plot and autoplot methods.
the graphics are prettier thanks to the package scales.
the plot and autoplot methods now have xlab, ylab, start, end, col, lty, show.legend, main and mar arguments. The autoplot methods have also a theme argument.
removed the c++ code to improve readability.
most of the stats methods for time-series now coerce twoStepsBenchmarks or rateSmooths into time-series.
reUseBenchmark now induces a set.smoothed.part element in model.list if reeval.smoothed.part is FALSE.
threeRuleSmooth makes it easier than bflSmooth to procede to a rate smooth.

various optimizations including cache for bflSmooth, which is now much faster, and alternative internal methods for time-series.
added a weights arg to bflSmooth, that reproduces the lissage en taux methodology.
the praislm and twoStepsBenchmark summaries now print some disclaimer to tell if the regression includes a differenciation.