In this work we present a study on the analysis of a large data set from seismology. A set of different large margin classifiers based on the well-known support vector machine (SVM) algorithm is used to classify the data into two classes based on their magnitude on the Richter scale. Due to the...

In this paper we demonstrate that a higher-ranking principal component of the predictor tends to have a stronger correlation with the response in single index models and sufficient dimension reduction. This tendency holds even though the orientation of the predictor is not designed in any way to...

This paper examines the problem of order selection in connection to the forecasting performance for vector autoregressive (VAR) processes. For this purpose we present a generalisation of the modified divergence information criterion (MDIC) for VAR models and compare it with traditional...

In this paper, we propose a test of fit based on maximum entropy. The asymptotic distribution of the proposed test statistic is established and a corrected form for small and medium sample sizes is furnished. The performance of the test is investigated through extensive Monte Carlo simulations....