A Comparative Study of Nonparametric Kernel estimators with Gaussian Weight Function (original) (raw)
2021
Abstract
Nowadays, Parametric methods become unfavorable by researchers because of the restrictions on using them and losing the flexibility in estimating and analysis the data. Therefore, the researchers preferred the nonparametric method which proved their efficiency and capable to analysis the data without of predetermined assumptions. Consequently, the data and their included information are becoming who determine the functional shape for the studied population and there are no parameters instead of the observations. The objective of estimating the nonparametric regression function is to approximate the regression function to the real regression function. On the other hand, COVID-19 pandemic nowadays speared in all the countries one of them is Iraq. The function of infection speared have been studied in different countries but not in Iraq. Therefore, the aim of our research is to apply three nonparametric Kernel estimators with Gaussian weighted function to model and forecast the number ...
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