Multiple-stratum intelligence models
You are making two mistakes, one in relation to the identification of the factors or what they represent (and factor analyzes have to be studied a lot by correlations with the tasks that each factor represents). And two, the relationships between the factors.

You do not take into account that each factor would represent very different abilities or processes (for example, the closing speed and the sequential reasoning is very different), the factors can be independent of this way, there does not have to be a linear relationship and in case if correlation exists, it will be correlation for a specific task, which leads me to indicate that it is proposing wrong relationships about completely different abilities or processes. This should clarify and is the model to start studying the factorial analysis: 

x1 = a1.F1 + a2.F2 ... + b1.S1 + c1.E1

x2=...

x3=...

x1 (score on the task of a specific person) = a1 (factorial weight of common factor). F1 (common factor) + a2.F2 .... + b1 .S (specific factor) + c (factorial weight of the error factor) + E1 (error)

(In the majority of analyzes, an error for a specific factor is not studied)