6.5 Relative importance metrics

Another approach to linear regression with multiple collinear regressors is to compute relative importance metrics8. The relaimpo package will compute the relative importance metrics and provides plotting.

This gives a somewhat different picture with year, Trachurus and the effort metrics most important while the environmental variables have low importance.

reli <- relaimpo::calc.relimp(anchovy~.,data=df)
plot(reli)

The pattern remains the same without Year as a response variable.

reli <- relaimpo::calc.relimp(anchovy~.-Year,data=df)
plot(reli)

  1. Groemping, U. (2006) Relative Importance for Linear Regression in R: The Package relaimpo Journal of Statistical Software 17, Issue 1. Downloadable at http://www.jstatsoft.org/v17/i01↩︎