# New version of analogue (0.8-0)

Yesterday I pushed an update of my analogue package to CRAN. The new version is 0.8-0 and contains some new functions, several bug fixes and a major change arising from additions to R 2.14.x requiring all packages to have a namespace. analogue now has its own namespace rather than relying on the one R would automagically generate if it weren’t provided. 0.8-0 is a moderate update to analogue containing some new functionality, some of which is there for testing/experimentation (like the fancy principal components regression).

The main user visible changes are:

`crossval()`

new function to perform leave-one-out, k-fold, n k-fold, and bootstrap cross-validation on transfer function models. A method for wa() models is provided.`pcr()`

performs principal components regression. Designed to allow transformations in the spirit of Legendre & Gallagher (2001, Oecologia) that allow PCA to be usefully applied to species data.`varExpl()`

and`gradientDist()`

are two new functions that extract the amount or variance explained by ordinations axes and the distances or locations along ordination axes. Methods currently available for`cca()`

and`prcurve()`

objects.`weightedCor()`

implements one of the tests from Telford & Birks (2011, QSR) based on the weighted correlation of WA optima and constrained ordination species scores.`Stratiplot()`

now handles absolute data better following a few bug fixes and general improvements in the underlying code.`panel.Stratiplot()`

gains new arguments`gridh`

and`gridv`

to allow user control of the grid lines on panel if plotted.`mat()`

gains a new argument `kmax` which can be used to limit the number of analogues considered as models when fitting MAT transfer functions. By default,`mat()`

considers models with 1 through to n-1 analogues (n = number of sites).`kmax`

can control this upper limit which will speed up fitting models, especially for large training sets. Invariably one wouldn’t want to average over entire training sets to produce predictions, or even over large numbers of analogues.

There were also many bug fixes and minor enhancements. Full details can be found in the ChangeLog, the relevant portion of which is appended below. Several development releases were made on R-forge after the 0.7-0 release to CRAN. These development versions were not publicly released, but the changes they implemented are all present in 0.8-0 of analogue.

```
Version 0.8-0
* Updated Example test checks and packaged for release to CRAN
Jan 11, 2012.
Version 0.7-7
* mat: new argument `kmax` can be used to limit the number of
analogues considered as models when fitting MAT transfer
functions. By default, `mat()` considers models with 1 through
to n-1 analogues (n = number of sites). `kmax` can control this
upper limit which will speed up fitting models, especially for
large training sets. Invariably one wouldn't want to average
over entire training sets to produce predictions, or even over
large numbers of analogues. As such I may set an upper limit for
the default value of `kmax` before this is released to CRAN.
* cumWmean, cummean: as a result of the above addition of `kmax`,
these two functions now take a `kmax` argument also. The default
behaviour is unchanged however.
* chooseTaxa: `type = "OR"` was not working due to a typo. It
returned the same as `type = "AND"`.
Version 0.7-6
* Stratiplot: Handling of absolute data types was broken. Fix
applied that should allow this to work if there are only
absolute scale variables or a mix or relative and absolute
data. All reletaive data should be unaffected.
* panel.Stratiplot: gains arguments `gridh` and gridv` which
control the number of horizontal and vertical grid lines used
on each panel. These correspond to the `h` and `v` arguments of
`panel.grid` in the Lattice package. The default is `-1` for
both, which attempts to align the grid lines with the tick marks.
Version 0.7-5
* weightedCor: implements one of the tests from Telford & Birks
(2011, QSR) based on the weighted correlation of WA optima and
constrained ordination species scores. Has a plot method.
* rdaFit: Non-user (currently) function that implements RDA
without all of the overhead of vegan::rda. As such it doesn't
compute PCA axes and does not return all the components described
by ?cca.object in package vegan. This function is used principally
in weightedCor(). Has a scores() method. rdaFit() is not
documented as the exact details of the function and its
capabilities remain to be determined.
Version 0.7-4
* gradientDist: new function to extract locations along an
ordination axis. Methods for prcurve() and cca().
* varExpl: new function to extract the amount of variance
explained by ordination axes. Currently methods for prcurve() and
cca() are available.
* Namespace: analogue now has an explicit name space in
preparation for R 2.14.0-to-be. Hence analogue now depends on
Vegan >= 1.17-12.
Version 0.7-3
* pcr: coef(), fitted(), residuals(), eigenvals(), performance(),
and screeplot() methods added.
Version 0.7-2
* pcr: new function pcr() performs principal components
regression. Designed to allow transformations in the spirit of
Legendre & Gallagher (2001) that allow PCA to be usefully
applied to species data.
Version 0.7-1
* crossval: new function to perform leave-one-out, k-fold,
n k-fold, and bootstrap cross-validation on transfer function
models. A method for wa() models is provided.
* tests: package now has a test that the examples continue to
return correct output.
```