JMASM algorithms and code algorithm for combining robust and bootstrap in multiple linear model regression (SAS)
The aim of bootstrapping is to approximate the sampling distribution of some estimator. An algorithm for combining method is given in SAS, along with applications and visualizations.
Saved in:
Main Authors: | Wan Muhamad Amir, Mohamad Shafiq, Hanafi A. Rahim, Puspa Liza Ghazali, Azlida Aleng, Abdullah, Z. |
---|---|
Format: | Non-Indexed Article |
Published: |
JMASM Inc.
2016
|
Online Access: | http://discol.umk.edu.my/id/eprint/8421/ http://digitalcommons.wayne.edu/jmasm/vol15/iss1/46/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
by: Wan Ahmad, Wan Muhamad Amir, et al.
Published: (2016) -
JMASM41: An alternative method for multiple linear model regression modeling, a technical
combining of robust, bootstrap and fuzzy approach (SAS)
by: Wan Ahmad, Wan Muhamad Amir, et al.
Published: (2016) -
JMASM 46: Algorithm for comparison of robust regression methods in multiple linear regression by weighting least Square Regression
by: Mohd Ibrahim, Mohamad Shafiq, et al.
Published: (2017) -
JMASM37: Simple Response Surface
Methodology Using RSREG (SAS)
by: Wan Ahmad, Wan Muhamad Amir, et al.
Published: (2016) -
Robust bootstrap methods in logistic regression model
by: Ariffin, Syaiba Balqish, et al.
Published: (2012)