A new method for computing exact experimental designs for linear regression models by integer quadratic programming is proposed. The key idea is to use the criterion of DQ-optimality, which is a quadratic approximation of the criterion of D-optimality in the neighbourhood of the approximate...

The estimation of multivariate GARCH time series models is a difficult task mainly due to the excessive parametrization exhibited by the problem, usually referred to as the “curse of dimensionality”. For the VEC family, the number of parameters involved in the model grows as a polynomial of...

Trend breaks appear to be prevalent in macroeconomic time series. Consequently, to avoid the catastrophic impact that unmodelled trend breaks have on power, it is standard empirical practice to employ unit root tests which allow for such effects. A popularly applied approach is the infimum...

Correlations between random variables play an important role in applications, e.g. in financial analysis. More precisely, accurate estimates of the correlation between financial returns are crucial in portfolio management. In particular, in periods of financial crisis, extreme movements in...

Three-way Candecomp/Parafac (CP) is a three-way generalization of principal component analysis (PCA) for matrices. Contrary to PCA, a CP decomposition is rotationally unique under mild conditions. However, a CP analysis may be hampered by the non-existence of a best-fitting CP decomposition with...

Finding a tube of small width that covers a certain percentage of the training data samples is a robust way to estimate a location: the values of the data samples falling outside the tube have no direct influence on the estimate. The well-known ν-tube Support Vector Regression (ν-SVR) is an...

Bayesian model averaging (BMA) is a statistical method for post-processing forecast ensembles of atmospheric variables, obtained from multiple runs of numerical weather prediction models, in order to create calibrated predictive probability density functions (PDFs). The BMA predictive PDF of the...

In the context of nonlinear models, the analytical expression of the Fisher information matrix is essential to compute optimum designs. The Fisher information matrix of the random effects logistic regression model is proved to be equivalent to the information matrix of the linearized model,...

A variety of existing symmetric parametric models for 3-D rotations found in both statistical and materials science literatures are considered from the point of view of the “uniform-axis-random-spin” (UARS) construction. One-sample Bayes methods for non-informative priors are provided for...

Smoothly time-varying (TV) GARCH models via an asymmetric logistic function mechanism are proposed, which are incorporated into the conditional volatility equation for capturing smooth structural breaks in the volatility of financial time series. The proposed models allow smooth transitions of...