White heteroscedasticty testing after outlier removal
Given the effect that outliers can have on regression and specification testing, a vastly used robustification strategy by practitioners consists in: (i) starting the empirical analysis with an outlier detection procedure to deselect atypical data values; then (ii) continuing the analysis with the s...
Main Authors: | Berenguer Rico, V, Wilms, I |
---|---|
Format: | Working paper |
Published: |
University of Oxford
2018
|
Similar Items
-
Heteroscedasticity testing after outlier removal
by: Berenguer-Rico, V, et al.
Published: (2020) -
Normality testing after outlier removal
by: Berenguer-Rico, V, et al.
Published: (2023) -
Persistence-based clustering with outlier-removing filtration
by: Alexandre Bois, et al.
Published: (2024-04-01) -
Nearest Centroid Classifier with Outlier Removal for Classification
by: Aditya Hari Bawono, et al.
Published: (2020-02-01) -
Thresher: determining the number of clusters while removing outliers
by: Min Wang, et al.
Published: (2018-01-01)