Partial Least Squares (PLS) methods are particularly suited to the analysis of relationships
between measures of brain activity and of behavior or experimental design. In …

In quantum mechanochemistry, quantum chemical methods are used to describe molecules
under the influence of an external force. The calculation of geometries, energies, transition …

With recent advances, neural networks have become a crucial building block in intelligent
IoT systems and sensing applications. However, the excessive computational demand …

The construction of a meaningful graph plays a crucial role in the success of many graph-
based representations and algorithms for handling structured data, especially in the …

An accessible guide to the multivariate time series tools used in numerous real-world
applications Multivariate Time Series Analysis: With R and Financial Applications is the …

A brand new, fully updated edition of a popular classic on matrix differential calculus with
applications in statistics and econometrics This exhaustive, self-contained book on matrix …

"... this edition is useful and effective in teaching Bayesian inference at both elementary and
intermediate levels. It is a well-written book on elementary Bayesian inference, and the …

The last several years have seen a growth in the number of publications in economics that
use principal component analysis (PCA) in the area of welfare studies. This paper explores …

There is strong evidence of structural changes in macroeconomic time series, and the
forecasting performance is often sensitive to the choice of estimation window size. This …

This paper offers a theoretical explanation for the stylized fact that forecast combinations
with estimated optimal weights often perform poorly in applications. The properties of the …