Environmetrics laboratory
 
About the Lab Computer Programs Publications
 
 

Computer Programs

The following programs can be used to perform the statistical methods and procedures described in the corresponding publications. They can be run within the Matlab computer program or as a standalone application. It is recommended that you read the user's guide carefully before using these programs.
 
Modified F-Test For Multiple Correlation Analysis with Spatial Data

                                                                                                                       Dutilleul, P., Pelletier, B. and Alpargu, G. 2008. Modified F tests for assessing the multiple correlation between one spatial process and several others. Journal of Statistical Planning and Inference, 138:1402-1415.


The program can be downloaded as Matlab (.p) files or as a standalone application.

Files for Matlab users: Files for non-Matlab users (standalone application):
 

Coregionalization Analysis with a Drift

Pelletier, B., Dutilleul. P., Larocque, G. and Fyles, J.W. 2009a. Coregionalization analysis with a drift for multi-scale assessment of spatial relationships between ecological variables 1.Estimation of drift and random components. Environmental and Ecological Statistics, 16:439-466.

Pelletier, B., Dutilleul. P., Larocque, G. and Fyles, J.W. 2009b. Coregionalization analysis with a drift for multi-scale assessment of spatial relationships between ecological variables 2. Estimation of correlations and coefficients of determination. Environmental and Ecological Statistics, 16:467-494.

 

Files for non-Matlab users:

 
Modified t-Tests in the Linear Model of Coregionalization


Dutilleul, P. and Pelletier, B. 2011. Tests of significance for structural correlations in the linear model of coregionalization. Mathematical Geosciences, 43:819-846.


Files for non-Matlab users:

 

 

Modified F-Tests for Redundancy Analysis with Spatial Data


Dutilleul, P. and Pelletier, B. 2017. A valid parametric test of significance for the average R^2  in redundancy analysis with spatial data. Spatial Statistics, 19:21-41.


Files for Matlab users: