Abstract Geodetic measurements rely on high-resolution sensors, but produce data sets with many observations which may contain outliers and correlated deviations. This paper proposes a powerful solution using Bayesian inference. The observed is modeled as multivariate time series stationary autoregressive (VAR) process t-distribution for white noise. Bayes’ theorem integrates prior knowledge. P...

Statistics ANOVA and related Multiple imputation Basic statistics Multivariate analysis of variance and Binary outcomes related techniques Categorical outcomes Nonlinear regression Censored and truncated regression models Nonparametric statistics Cluster analysis Ordinal outcomes Correspondence analysis Other statistics Count outcomes Pharmacokinetic statistics Discriminant analysis Power and s...

We propose an efficient semiparametric estimator for the multivariate linear quantile regression model in which the conditional joint distribution of errors given regressors is unknown. The procedure can be used to estimate multiple conditional quantiles of the same regression relationship. The proposed estimator is asymptotically as efficient as if the conditional distribution were known. Simu...