Abstract: The multivariate estimation problems arise if the observations are available for several related variables of interest. The multivariate time series may be found in many fields of ...

Brain activities often follow an exponential family of distributions. The exponential distribution is the maximum entropy distribution of continuous random variables in the presence of a mean. The ...

A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...

In this repository, using the statistical software R, are been analyzed robust techniques to estimate multivariate linear regression in presence of outliers, using the Bootstrap, a simulation method ...

This paper studies nonparametric estimation of parameters of multivariate Hawkes processes. We consider the Bayesian setting and derive posterior concentration rates. First, rates are derived for ...

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...

Bayesian Optimization, widely used in experimental design and black-box optimization, traditionally relies on regression models for predicting the performance of solutions within fixed search spaces.

Abstract: Multifractal analysis has become a reference tool for signal and image processing. Grounded in the quantification of local regularity fluctuations, it has proven useful in an increasing ...

When modeling sparsely observed multivariate data, strong prior information elicited from experts can be used to bolster predictive accuracy and counteract sampling bias. Similarly, modeling ...