Ng, Kelvin Sai-cheong

2017-Jul-12 05:47 UTC

### [R] How to formulate quadratic function with interaction terms for the PLS fitting model?

Dear all, 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 data(gasoline) 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[0] * NIR[0,i] + a[1] * NIR[1,i] + ... I want to fit the data with: octane[i] = a[0] * NIR[0,i] + a[1] * NIR[1,i] + ... + b[0]*NIR[0,i]*NIR[0,i] + b[1] * 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? Thanks, Kelvin [[alternative HTML version deleted]]

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