Skip to Main Content
Data Analysis and Statistics for Geography, Environmental Science, and Engineering
book

Data Analysis and Statistics for Geography, Environmental Science, and Engineering

by Miguel F. Acevedo
December 2012
Beginner content levelBeginner
557 pages
19h 5m
English
CRC Press
Content preview from Data Analysis and Statistics for Geography, Environmental Science, and Engineering
516 Data Analysis and Statistics for Geography, Environmental Science, and Engineering
standardized and shifted positive, i.e., frag.ss that we generated in the previous chapter. Select
for Y the rst three variables (POC, PRL, LAI) and for X the last six variables, or fragmentation
metrics (NP, PD, MPS, LPI, MSI, MPFD).
Apply cca function
> X <- frag.ss[,4:9]; Y<-frag.ss[,1:3]
> XY.cca <- cca(X,Y)
> XY.cca
Call: cca(X = X, Y = Y)
Inertia Proportion Rank
Total 0.3183 1.0000
Constrained 0.1818 0.5713 3
Unconstrained 0.1365 0.4287 5
Inertia is mean squared contingency coefficient
Eigenvalues for constrained axes:
CCA1 CCA2 CCA3
0.095851 0.084667 0.001307 ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Applied Modeling Techniques and Data Analysis 1

Applied Modeling Techniques and Data Analysis 1

Yannis Dimotikalis, Alex Karagrigoriou, Christina Parpoula, Christos H. Skiadas
Geospatial Data and Analysis

Geospatial Data and Analysis

Aurelia Moser, Jon Bruner, Bill Day

Publisher Resources

ISBN: 9781439885017