[R] How to formulate quadratic function with interaction terms for the PLS fitting model?
Ng, Kelvin Sai-cheong
kscng at connect.hku.hk
Wed Jul 12 07:47:51 CEST 2017
I am using the pls package of R to perform partial least square on a set of
multivariate data. Instead of fitting a linear model, I want to fit my
data with a quadratic function with interaction terms. But I am not sure
how. I will use an example to illustrate my problem:
Following the example in the PLS manual:
## Read data
gasTrain <- gasoline[1:50,]
## Perform PLS
gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO")
where octane ~ NIR is the model that this example is fitting with.
NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse
reflectance measurements from 900 to 1700 nm.
Instead of fitting with octane[i] = a * NIR[0,i] + a * NIR[1,i] + ...
I want to fit the data with:
octane[i] = a * NIR[0,i] + a * NIR[1,i] + ... +
b*NIR[0,i]*NIR[0,i] + b * NIR[0,i]*NIR[1,i] + ...
i.e. quadratic with interaction terms.
But I don't know how to formulate this.
May I have some help please?
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