PLS-PM has been described as a non-parametric technique which makes no distributional assumptions and can be estimated with small sample sizes. Moreover, it is a prediction-based approach which aims at maximizing dependent variables’ explained variance by adopting an ordinary least squares estimation (OLS) method.

How is it possible to be non-paramentric and at the same time to adopt an OLS which by definition requires weel defined assumptions?

Thanks for the attention