windrose
vignette might be nice.
... started a separate vignette for tsplot
, implement separate
vignettes for windrose
and image
.summary(..., detailed = TRUE)
does not show sigma coefficients.mfcol
to ncol
, adjusted handling of
labels/legends.0.1-6
, tsplot()
fix: Should be implemented everywhere?tsplot()
for temperature difference can now deal with all-missing (shows NO DATA)windrose.foehnix
plotting routine which - by default -
centers the sector around north by shifting the sector by one half of the
interval selected (default is 10). Thus, the most northern sector internally
got defined as [-interval/2, interval/2]
but forgot to take into account
the data 360 - interval / 2
. Should be fixed now.demodata()
when loading multiple stations.summary.foehnix()
when no inflation happened (sprintf error)IGN
(ignorance) as alternative score.pkgdown
site: combined README.md
(index.html
and
github readme), removed "getting started", added demo data sets and vignette
"Import data".image.foehnix
(custom xlim
and ylim
,
allow for custom style
files).image.foehnix
.usethis
; reduces package size; added data/scripts in data-raw
.image
function (image.foehnix
) to R/image.R
.image
allows to set custom xlim
, ylim
(and zlim
) limits.
Decreasing xlim
values allow to plot over the new years period.write.csv
method to save estimated probabilities to a CSV file.
Will be ued to test output (and compare R/python implementation).windrose
.windrose.default
.demodata(...)
function to be able to handle both
(multiple) demo data sets.ellboegen
, sattelberg
, viejas
, luckyfive
) now stored
as binary time series objects (.rda
; zoo
).summary.crch
(abs
was missing).summary.foehnix
(similar to flexmix
)."posterior"
, 5L
) in plot.foehnix
.foehnix_filter
. Only rows used have to be
checked (controlled by new input argument \code{cols}).tsplot
)tsplot
: wind sectors, styles, better customization options
(tsplot.control
).image.foehnix
); further adjustments
required.uv2ddff
and ff2dduv
now return a zoo
object if the input
is a single zoo
object (uv2ddff(data)
or ddff2uv(data)
where data
is of class zoo
).logitX
model.matrix.lambda
) from the foehnix
interface.
iwls_logit
would, technically, allow for iterative penalized
estimates but is rather slow. Thus, an experimental control argument
for regularized estimates based on the glmnet
package has been
implemented (see \code{\link{foehnix.control}}/\code{\link{glmnet.control}}).windrose.default
allows for custom data filters (using the foehnix filter
method) and custom variable names for wind direction and wind speed
(var.dd
/var.ff
). Default var.dd = "dd"
and var.ff = "ff"
.
Custom filters only allowed with multivariate objects (zoo or data.frame).windrose
allows to specify custom names.tsplot
allows to specify custom variable names (rename defaults).
Requires some more testing.foehnix
objects (returned by foehnix
) contain a new element
nobs
, the number of elements used for classification.
Note that this is not the same information as provided by
the good
, the bad
, and the ugly
from the foehnix filter
(the filter_obj
only contains information based on the variables
used with the filter, not on the covariates used for the foehnix
model).windrose
manual extended, windrose
also allows to plot a windrose
of non-foehnix
objects (e.g., univariate zoo objects of dd
and ff
or two numeric vectors). Examples included.foehnix_filter
where observations (rows) where not
all elements have been NA have been treated as "outside wind sector"
rather than "not all observations available" (FALSE has been returned
instead of NA; now an NA will be returned by if multiple filters are
used and at least one element is missing).N_inflated
was missing when no inflation was needed.iwls_logit
: renamed variable mu
to prob
.image.foehnix
) with some
features. Has to be seen as "under development" at the moment!Getting Started
, Statistical Model
,
and References
.predict.foehnix
, new phoenix_filter
was not yet implemented.plot.foehnix
method
(colors/line types/labeling), added log = FALSE
option to plot the
paths on the EM iteration scale rather than the log iteration scale.windfilter
is used as an argument to the method foehnix
the
script will now shout at you! Depricated option (this check should
be removed before release).ddff2uv
and uv2ddff
(plotting).windrose
and probwindrose
plotting functions,
however, not yet production ready. TODO!prob
($\pi$) for the non-commitant mixture model
is now mean(z)
rather than 0.5
.windfilter
renamed to filter
when calling foehnix
!foehnix_filter
has been extended. So far an integer vector has
been returned with the observations within filter (the 'good' ones).
This made it hard to find out which ones have to be set to 0
(where both, y
was ont NA
and all variables for the filter(s)
were not NA
). I made the return of the foehnix_filter
slightly
more complex. foehnix_filter
now returns an object of class
foehnix.filter
, a list with three elements containing
integer vectors which correspond to the row indizes of the data
(input x
, see foehnix_filter
manual).
Returns:good
: observations/rows within filterbad
: observations outside filter, but all values required for the
filter have been available (not NA
).ugly
: if at least one of the variables used for the filter was
missing.switch = TRUE
option. Simply
use z = f(y <= mean(y))
instead of z = f(y >= mean(y))
when initializing the component membership to flip the components.Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.