The calibration method PLS1 is described in terms of the joint covariance structure of the explanatory variables and the predicted variable. In the population version it is possible to give simple ...

All of the predictive methods implemented in PROC PLS work essentially by finding linear combinations of the predictors (factors) to use to predict the responses linearly. The methods differ only in ...

The process of using past cost information to predict future costs is called cost estimation. While many methods are used for cost estimation, the least-squares regression method of cost estimation is ...

To find approximations for bias, variance and mean-squared error of least-squares estimators for all coefficients in a linear dynamic regression model with a unit ...

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can use R-style formulas. First, you need to import statsmodels and its ...

In a multivariate regression model, the errors in different equations may be correlated. In this case the efficiency of the estimation may be improved by taking these cross-equation correlations into ...