While standard minimum squares (OLS) regression remains a cornerstone in statistical evaluation, its requirements aren't always fulfilled. Therefore, exploring substitutes becomes critical, especially when confronting with curvilinear patterns or violating key assumptions such as average distribution, homoscedasticity, or autonomy of residuals. Pos

While Ordinary Least Squares (OLS) remains a foundational technique/method/approach in regression analysis, its limitations sometimes/frequently/occasionally necessitate the exploration/consideration/utilization of alternative methods. These alternatives often/may/can provide improved/enhanced/superior accuracy/fit/performance for diverse/varied/un