Browsing by Subject "Outliers (Statistics)"
Now showing items 1-2 of 2
(National Institute of Development Administration, 2010);
An important problem often found in a regression analysis is that a structural change in regression exists and/or the observed data contain outliers. These can lead to a violation of the Gauss-Markov assumptions and affect least squares (LS), rendering the regression inadequate. In this dissertation, an alternative regression model has been constructed from a combination of two principle ideas, namely the Tobit and piecewise regressions. This combined model, called the Tobit-piecewise (TP) regression model, can be suitably applied to cope with ...
(National Institute of Development Administration, 2009);
In linear models, the ordinary least squares estimators of have always turned out to be the best linear unbiased estimates. When the sample data contain outliers, the outliers may have a considerable effect on the least-squares estimates of , and an alternative approach to the problem is needed to obtain a better fit of the model or more precise estimates of . In this study, new weights were constructed for the sample data from two new influence functions and applied in the estimation of regression coefficients with outliers. Two sets of ...