Package index

All functions

FS()

Default forward selection function.

FS(<dcca>)

Forward selection of traits or environmental variables using dc-CA.

FS(<wrda>)

Forward selection of predictor variables using wrda or cca0

anova(<cca0>)

Permutation Test for canonical correspondence analysis

anova(<dcca>)

Community- and Species-Level Permutation Test in Double Constrained Correspondence Analysis (dc-CA)

anova(<wrda>)

Permutation Test for weighted redundancy analysis

anova_sites()

Utility function: community-level permutation test in Double Constrained Correspondence Analysis (dc-CA)

anova_species()

Utility function: Species-level Permutation Test in Double Constrained Correspondence Analysis (dc-CA)

cca0()

Performs a canonical correspondence analysis

coef(<dcca>)

Coefficients of double-constrained correspondence analysis (dc-CA)

dc_CA()

Performs (weighted) double constrained correspondence analysis (dc-CA)

dune_trait_env

Dune meadow data with plant species traits and environmental variables

fCWM_SNC()

Calculate community weighted means and species niche centroids for double constrained correspondence analysis

fN2()

Hill number of order 2: N2

fitted(<dcca>)

Fitted values of double-constrained correspondence analysis (dc-CA)

getPlotdata()

Utility function: extracting data from a dc_CA object for plotting a single axis by your own code or plot.dcca.

ipf2N2()

Iterative proportional fitting of an abundance table to Hill-N2 marginals

plot(<dcca>)

Plot a single dc-CA axis with CWMs, SNCs, trait and environment scores.

plot_dcCA_CWM_SNC()

Plot the CWMs and SNCs of a single dc-CA axis.

plot_species_scores_bk()

Vertical ggplot2 line plot of ordination scores

predict(<dcca>)

Prediction for double-constrained correspondence analysis (dc-CA)

predict(<wrda>)

Prediction from cca0 and wrda models

print(<dcca>)

Print a summary of a dc-CA object.

print(<wrda>)

Print a summary of a wrda or cca0 object

scores(<dcca>)

Extract results of a double constrained correspondence analysis (dc-CA)

scores(<wrda>)

Extract results of a weighted redundancy analysis (wrda) or a cca0 object.

wrda()

Performs a weighted redundancy analysis