A Generalized Ratio-cum-Product Estimator of Finite Population Mean in Stratified Random Sampling
This paper suggests a ratio-cum product estimator of a finite population mean using information on the coefficient of variation and the fcoefficient of kurtosis of auxiliary variate in stratified random sampling. Bias and MSE expressions of the suggested estimator are derived up to the first degree of approximation. The suggested estimator has been compared with the combined ratio estimator and several other estimators considered by Kadilar and Cingi (2003). In addition, an empirical study is also provided in support of theoretical findings.
AbstractA very important aspect in sewer systems management is represented by the detection of illicit intrusions, which recently supported the development of online sensors for wastewater quality monitoring. The present paper proposes a new methodology for characterizing an illicit intrusion in a sanitary or combined sewer system, using on-line pollutant concentration measurements. The source identification is formulated as an optimization problem, solved combining the hydraulic and quality simulation tool storm water management model (SWMM) with the GALib code. The methodology, which includes a pre-screening procedure useful for complex and large systems, is applied to a literature scheme and a real test-case, showing promising results. An uncertainty analysis is also performed for checking its robustness with respect to inflow uncertainty and in the presence of measurement errors.