genus

Genus gives the abundance of 27 common tree genera in the
tropical moist forest of the Congo-Basin and 40
geo-referenced environmental variables on one thousand 8 by
8 km plots (observations). Each plot's data was obtained by
aggregating the data measured on a variable number of
previously sampled 0.5 ha sub-plots. Geo-referenced
environmental variables were used to describe the physical
factors as well as vegetation characteristics.  14 physical
factors were used pertaining the description of topography,
geology and rainfall of each plot. Vegetation is
characterized through 16-days enhanced vegetation index
(EVI) data.

SCGLR extends the Fisher Scoring Algorithm so as to combine PLS
    regression with GLM estimation in the multivariate context.

Guillaume Cornu

SCGLR

Supervised Component Generalized Linear Regression (SCGLR)

genus function

<tabular>ll</tabular>{
   <code>gen1 to gen27</code> 	abundance of the 27 common genera.<code>altitude</code> 	above-sea level in meters.<code>pluvio_yr</code> 	mean annual rainfall.<code>forest</code> 	classified into seven classes.<code>pluvio_1 to pluvio_12</code> 	monthly rainfalls.<code>geology</code> 	5-level geological substrate.<code>evi_1 to evi_23</code> 	16-days enhanced vegetation indexes.<code>lon and lat</code> 	position of the plot centers.<code>surface</code> 	sampled area.}

genus: Sample dataset of abundance of genera in tropical moist forest

Description

Arguments

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