Proposed method to estimate missing values in Non - Parametric multiple regression model | ||
| journal of Economics And Administrative Sciences/ University of baghdad | ||
| Article 1, Volume 22, Issue 89, April 2016, Pages 396-406 | ||
| Abstract | ||
| In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods | ||
| Keywords | ||
| non; Parametric Multiple Regression Model; missing observation; Missing Data Mechanisms; Patterns of Missing Data; Nadaraya; Least Squared Cross Validation; Nadary | ||
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