Accession Number : ADA124678


Title :   Robust Multiple Linear Regression.


Descriptive Note : Master's thesis,


Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING


Personal Author(s) : Sultan,Ahmed Mohamed M


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a124678.pdf


Report Date : Dec 1982


Pagination or Media Count : 73


Abstract : An extensive Monte Carlo analysis is conducted to determine the performance of robust linear regression techniques with and without outliers. Thirteen methods of regression are compared including least squares and minimum absolute deviation. The classical robust techniques of Huber, Hampel were studied and robust techniques using the Q-statistic as a discriminant were introduced. The model studied contained eleven variables with 27 observations. The error distributions considered were uniformly normally, double exponentially distributed. Least squares gave the best fit without outliers. In the presence of gross outliers a rejection of outliers technique gave the best fit. (Author)


Descriptors :   *MATHEMATICAL MODELS , *MONTE CARLO METHOD , *LINEAR REGRESSION ANALYSIS , METHODOLOGY , COMPARISON , STATISTICS , THESES , VARIABLES , ERROR ANALYSIS , LEAST SQUARES METHOD , TABLES(DATA)


Subject Categories : Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE