Investigate correlation between thickness/strength and long-term thermocline depth

[vildead]

Consider using another variable in models 1) replace thermocline depth by measure of general lake stratification (standard deviation of all temperatures) 2) replace thickness/strength by mean temperature gradient (slope of thermocline curve)

[vildead]

see report_01.Rmd

[vildead]

Investigate not just r but also significance of correlations

[rubenrabb01]

@vildead this link could be helpful for understading concurvity: https://stat.ethz.ch/R-manual/R-devel/library/mgcv/html/concurvity.html

Note that in our case, as we have discarded smooth surfaces of two time variables (ruled out seasonal features and keep long-term trend) concurvity should be come from high correlation between non-time covariates (i.e. co-linearity in the generalized linear approximation to gam models). Indeed, I've just checked the concurvity values for pike-day model and they are only below 0.5 for the variable "det_therm_deviation_center".

[rubenrabb01]

This paper of variable selection in GAMs is worth reading: https://www.sciencedirect.com/science/article/pii/S0167947311000491?via%3Dihub

[vildead]

@rubenrabb01 these are very nice resources! Thank you a lot :)

[vildead]

using caret::findCorrelation() was decided that the thickness and strength are going to be removed from model and replaced by mean temperature gradient