ANALYTICAL QUALITY ASSESSMENT OF ITERATIVELY REWEIGHTED LEAST-SQUARES (IRLS) METHOD
Abstract
The iteratively reweighted least-squares (IRLS) technique has been widely
employed in geodetic and geophysical literature. The reliability measures are
important diagnostic tools for inferring the strength of the model validation. An
exact analytical method is adopted to obtain insights on how much iterative
reweighting can affect the quality indicators. Theoretical analyses and numerical
results show that, when the downweighting procedure is performed, (1) the
precision, all kinds of dilution of precision (DOP) metrics and the minimal
detectable bias (MDB) will become larger; (2) the variations of the bias-to-noise
ratio (BNR) are involved, and (3) all these results coincide with those obtained by
the first-order approximation method.
employed in geodetic and geophysical literature. The reliability measures are
important diagnostic tools for inferring the strength of the model validation. An
exact analytical method is adopted to obtain insights on how much iterative
reweighting can affect the quality indicators. Theoretical analyses and numerical
results show that, when the downweighting procedure is performed, (1) the
precision, all kinds of dilution of precision (DOP) metrics and the minimal
detectable bias (MDB) will become larger; (2) the variations of the bias-to-noise
ratio (BNR) are involved, and (3) all these results coincide with those obtained by
the first-order approximation method.
Keywords
IRLS; Outlier; DOP; MDB; BNR
