Analyzing Compositional Data with R by K. Gerald Boogaart & Raimon Tolosana-Delgado

Author:K. Gerald Boogaart & Raimon Tolosana-Delgado
Language: eng
Format: epub
Publisher: Springer Berlin Heidelberg, Berlin, Heidelberg

5.3.1.3 Multiple and Multivariate Covariables

Thus, the dataset contains a mixture of continuous and categorical covariables. We can thus study the dependence of composition on one or two continuous variables with regression, or else we can study the influence of the factors with ANOVA or finally get a complete model with both continuous and discrete covariables integrated.

In the next section, displaying the dependence, we will see that two different covariables (relief and grain) have a significant influence. This will give rise to several questions: How do we model the joint influence of all relevant covariables?

What composition would be predicted if both relief and grain are known?

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