This book presents Bayes' theorem, the estimation of unknown parameters, the
determination of confidence regions and the derivation of tests of hypotheses for the …

The goal of this paper was to perform an exhaustive search regarding which combination of
minimum L1-norm (MinL1) criteria is a better option for outlier identification. By means of …

Robust estimation has proved to be a valuable approach to adjust a surveying network
when there are systematic or gross errors in the observations or systematic errors in the …

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted
observations and autocorrelated random deviations. This colored noise is represented by a …

Outlying observations are undesirable but possible elements of geodetic measurements. In
such a context, the primary and trivial solution is to repeat “suspected” observations. The …

The variants of Msplit estimation proposed so far are based on the objective function related
to the least-squares method and hence they are known as the squared Msplit estimation. We …

Satellite interferometric synthetic aperture radar (InSAR) has become a recognized and
reliable surface deformation monitoring technology in recent years. However, the complexity …

The efficacy of robust M-estimators is a well-known issue when dealing with observational
blunders. When the number of observations is considerably large—long time series for …

Robust estimators are often lacking a closed‐form expression for the computation of their
residual covariance matrix. In fact, it is also a prerequisite to obtain critical values for …

The goal of this paper is to evaluate the outlier identification performance of iterative Data
Snooping (IDS) and L1-norm in levelling networks by considering the redundancy of the …