Comparison between some of methods for monotone nonparametric regression | ||
| Al Kut Journal of Economics Administrative Sciences | ||
| Article 1, Volume 0, Issue 0, January 2018, Pages 116-124 | ||
| Abstract | ||
| ABSTRACT:- This research was concerning to study monotone nonparametric methods for estimating the nonparametric regression function (i.e treatment outlier) to achieve a monotone function (nonincreasing). So we will use the monotone methods to treatment outlier but after estimate the regression function with use kernel estimator (local linear regression ) these methods are:- 1- Mukerjee method takes averages of maximums and minimum of subsets of the data was used to adjust the initial kernel regression estimates 2- Algorithm least square isotonic regression called (PAV) . 3- use the researcher special case when . In the experimental aspect comparison was done of which is the best methods through the simulation procedure using)Monte Carlo( method.In both aspects we use two of the important statistical measures which are Mean square error (MSE) and efficiency. | ||
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