TY - JOUR
AU - HAMMOND,, K.
AB - Abstract A robust analysis for field data is proposed using a stratified rank regression model. That analysis follows Pettitt (1982). Alternatively, a new technique is described where residuals are log gamma random variables. The log gamma distribution is approximately normal when the shape parameter is large and this parameter is taken as an integer which is either preselected or estimated by a simple grid search. Algorithms for estimating location parameters by maximizing the likelihood based on within-stratum rank information are described and illustrated using a small data set. This content is only available as a PDF. © 1988 Biometrika Trust
TI - Rank regression with log gamma residuals
JO - Biometrika
DO - 10.1093/biomet/75.4.741
DA - 1988-12-01
UR - https://www.deepdyve.com/lp/oxford-university-press/rank-regression-with-log-gamma-residuals-MzaftBYWe9
SP - 741
EP - 751
VL - 75
IS - 4
DP - DeepDyve
ER -