The identification of the out of control variable, or variables, after a multivariate control chart signals, is an appealing subject for many researchers in the last years. In this paper we propose a new method for approaching this problem based on principal components analysis. Theoretical...

Most processes involve more than one process/product output variable, multiple process input/regulatory variables, and a category of noise variables, which consists of factors not considered in the model, or those external to the process. Since output variables are not necessarily independent of...

Motivated by the conjectured existence of trends in the intensity of tropical storms, this paper proposes new inferential methodology to detect a trend in the annual pattern of environmental data. The new methodology can be applied to data which can be represented as annual curves which evolve...

This paper describes a forecasting exercise of close-to-open returns on major global stock indices, based on price patterns from foreign markets that have become available overnight. As the close-to-open gap is a scalar response variable to a functional variable, it is natural to focus on...

The increasing exposure to renewable energy has amplified the need for risk management in electricity markets. Electricity price risk poses a major challenge to market participants. We propose an approach to model and fore- cast electricity prices taking into account information on renewable...

Abstract We introduce a functional factor model to investigate the dependence of cumulative return curves of individual assets on the market and other factors. We propose a new statistical test to determine whether the dependence in two sample periods are equal. The statistical properties of the...

Abstract The main purpose of the present paper is to investigate the problem of the nonparametric estimation of the expectile regression in which the response variable is scalar while the covariate is a random function. More precisely, an estimator is constructed by using the k Nearest Neighbor...