The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform this research, the need for detection and investigation of the impact of pollution of the Tigris River in Kut city was necessitated by wastewater, particularly TDS dealt as dependent variable, and the impact of three pollutants (PO4, CL, SO4) that represented explanatory variables. In order to achieve this goal, a sample of (91) samples was drawn and checked in the laboratory of the directors of Kut city. Root of Mean Squared Error: RMSE was used as comparison criterion.
Using the Maximum Likelihood Method with a Suggested Weight to Estimate the Effect of Some Pollutants on the Tigris River- City of Kut
Outliers
Trimmed Maximum Likelihood
River's Water Pollution
Weighted Regression Methods
Publication Date
Mon Apr 15 2024
Journal Name
Nibal