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ordinary least squares (OLS) under 36 different outlier data configurations. Two of the robust estimators, Least Absolute Value … predictor variables (2, 3 and 6), outlier density (0%, 5% and 15%) and outlier location (2x,2y s, 8x8y s, 4x,8y s and 8x,4y s …
Persistent link: https://www.econbiz.de/10009475082
methods utilised proved incapable of identifying or accommodating the gross outlier(s) in the data, the more successful …
Persistent link: https://www.econbiz.de/10009476844
Small area estimation techniques have typically relied on plug-in estimation based on models containing random area effects. More recently, regression M-quantiles have been suggested for this purpose, thus avoiding conventional Gaussian assumptions, as well as problems associated with the...
Persistent link: https://www.econbiz.de/10009457565
large number of factors and limited observations, even one outlier can adversely affect the results. Robust regression …
Persistent link: https://www.econbiz.de/10009464024
A single outlier in a regression model can be detected by the effect of its deletion on the residual sum of squares. An ….Our procedures, illustrated with four example, permit keen insights into the fragility of inferences to specific shocks, such as …
Persistent link: https://www.econbiz.de/10009441449
outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the …
Persistent link: https://www.econbiz.de/10009430179