The article introduces a new type of estimator to deal with multicollinearity in statistical models. This new estimator, called s–K type principal components estimators, includes well-known estimators like principal components regression (PCR). The researchers found conditions where the new estimator outperforms PCR and other existing estimators in terms of accuracy. They used simulations and examples to show how the new estimator works better in practice.