The package has undergone a major make-over. A slight, but breakable,
change in the api of fit_outlier
. The documentation of
fit_outlier
has been updated and now includes more and
better examples of how and when to use the function. The
fit_graph
function is no longer a part of
molic. It now lives in its own package at ess and molic
is now dependend on ess. It is therefore now required
to run include(ess)
to have access to
fit_graph
.
The readme file has also undergone a major change - the former
example using cars
data has been removed; it was never
really a good example showing how to do outlier detection with
molic.
derma
has been included and a new
vignette using this data has been added.tgp_dat
data has now been compressed to save disk
space.plot.gengraph
function applied to an object
(gengraph
) returned from one of the graph fitting functions
(fit_graph
, fit_components
etc.) now takes an
input that let the user specify the color of the nodes.subgraph
function is now provided.sapply'
s are now converted to vapply'
s for
safety and potentially more speed when fitting graphs.pmf
no longer plots the density of the deviances of a
outlier_model
object. Use plot
for this
instead; this is now consistent with the other related functions like
fit_outlier
. Instead pmf
is used to construct
the probability mass function of a decomposable graphical model which
can be used to obtain probabilities of observing specific
cells/observations/configurations.Development Model
From this release we adopt the branching model introduced by Vincent Driessen
This means, that there are now two branches: the master branch is always the current stable version, and the develop branch is the develop version.
New API
fit_outlier
that depends on an adjacency
list no accept gengraph
objects returned from
fit_graph
- i.e. no need to use adj_lst()
first.New functions
generate_multiple_models
fit_graph
and fit_outlier
that conducts
all the hypothesis \(H_k:\) \(y\) has level \(k\) for \(k =
1,2,\ldots, l\).plot.multiple_models
fit_multiple_models
this
function is used to visualize all the hypothesis tests for a single
observation simultaneously. It is a ggplot2
objectplot.outlier
fit_outlier
this function
is used to visualize the approximated density of the deviance under the
null hypothesis. It is a ggplot2
object.components
fit_components
Misc * All deviances are now non-negative as they should be! Before, a constant was neglected which could potentially confuse the users since a deviance is per definition non-negative.