When we perform an usual multiple linear regression analysis, we must check some assumptions like residuals are normally distributed, no multicollinearity of predictors and homoscedasticity. For each assumption, we usually perform a hypothesis test while trying to validate our model.
My question is the following one: If we perform a partial least squares regression analysis (PLSR model), do we need to check any assumptions? If so, which are these assumptions and how do we check them (are there any hypothesis tests that must be performed)? If there are no assumptions, why there are none?