NEWS
douconca 1.2.5 (2026-02-23)
- Minor update with cleaner version of function ipf2N2 or other minor changes.
douconca 1.2.4 (2025-10-14)
- Update of function ipf2N2 for informative pre-processing of abundance data.
The row and column marginals are set equal to Hill N2 or, the column
marginals to N2(1-N2/N), the effective number of informative species.
For max_iter==0 only the species marginal is adapted to N2 or N2(1-N2/N)
without further adjustment to the abundance table.
This is the simplest N2-preprocessing method and is generally quite powerful.
It might be particulary useful if the function did not converge or gives a warning
indicating very unequal site totals.
douconca 1.2.3 (2025-05-09)
- Forward selection of traits and of environmental variables added (function FS()).
- Function ipf2N2 for informative pre-processing of abundance data. The
row and column marginals are set equal to Hill N2 or, the column
marginals to 2N2(N-N2)/N, the effective number of informative species.
informative species
- More efficiency for large data sets by addition of a new cca function (cca0).
- An anova method for cca0 to enable residual predictor permutation.
- Improved stability for 'exceptional' data sets.
- The response can now be supplied as left-hand side of the environmental formula,
instead of by the response argument.
douconca 1.2.2 (2024-12-02)
- New coef.dcca() and fitted.dcca() functions with predict.dcca() adapted.
The function coef() can give fourth-corner correlations and regression
coefficients.
- Patch release with extended test files and associated small corrections,
for example, SDS (standard deviation of predictors)
was in v1.2.1 a constant factor too large with the default of the argument
divideBySiteTotals (the regression weights and t-values were correct).
douconca 1.2.1 (2024-09-25)
- Patch release addressing check errors on several CRAN build machines.
douconca 1.2.0 (2024-09-13)
douconca 1.1.6
- An issue with collinear predictors in v1.1.5 has been resolved.
douconca 1.1.5
- The package can now do general dc-CA, instead of the vegan-based version with
equal site weights only. For users of the previous version, the function
dc_CA_vegan has been replaced by the more general function dc_CA.
The default gives the same analysis. By specifying
the argument
divideBySiteTotals = FALSE, obtain the original dc-CA analysis
with unequal site weights.
- The
plot_dcCA function is now a method: plot.
- General dc-CA required weighted redundancy analysis. For this, a new function
wrda has been added, with methods for print, scores and anova.
- A
predict function has been added.
- A dc-CA can be computed from community-weighted means (CWMs) with
trait and environment data with species and site weights. See the new function
fCWM_SNC. This is of interest, for example, to make a dc-CA analysis
reproducible when the abundance data cannot be made public, and
it may also allow to perform dcCA with intra-species trait variation.
The user needs to be able to compute meaningful CWMs in this case and supply
trait data that reflect the (species-weighted) inter-trait covariance.
- Several functions are updated. In particular, there are corrections to
the anova function.
douconca 1.1.2
- The
scores.dccav function is corrected concerning intra-set correlations for
traits and environmental variables.
- The plotting functions are updated to avoid ggplot2 warnings on color and
size.
- The fitted straight lines in the plots use the implicit weights
(they did already, but the help said they did not).