Simultaneous confidence bands have been shown in the statistical literature as powerful inferential tools in univariate linear regression. While the methodology of simultaneous confidence bands for univariate linear regression has been extensively researched and well developed, no published work seems available for multivariate linear regression. This paper fills this gap by studying one partic...

Abstract. The aim of this contribution is to present a new, however rapidly developing domain of statistics – functional data analysis (FDA). A particular problem of extending multivariate regression to the functional setting is discussed. First of all, two real data sets and connected problems are presented. Multivariate regression is briefly recalled focusing mainly on the case of strongly co...

Extensions of linear cryptanalysis making use of multiple approximations, such as multiple and multidimensional linear cryptanalysis, are an important tool in symmetric-key cryptanalysis, among others being responsible for the best known attacks on ciphers such as Serpent and present. At CRYPTO 2015, Huang et al. provided a refined analysis of the key-dependent capacity leading to a refined key...

Abstract: Let {Sn = (Xn,Wn)}n≥0 be a random walk with Xn ∈ R and Wn ∈ Rm. Let τ = τa = inf{n : Xn > a}. The main results presented are two term asymptotic expansions for the joint distribution of Sτ and τ and the marginal distribution of h(Sτ/a, τ/a) in the limit a → ∞. These results are used to study the distribution of t-statistics in sequential experiments with sample size τ , and to remove ...

We generalize the linear rational expectations solution method of Whiteman (1983) to the multivariate case. This facilitates the use of a generic exogenous driving process that must only satisfy covariance stationarity. Multivariate cross-equation restrictions linking the Wold representation of the exogenous process to the endogenous variables of the rational expectations model are obtained. We...

We present a Bayesian approach for modeling multivariate, dependent functional data. To account for the three dominant structural features in the data—functional, time dependent, and multivariate components—we extend hierarchical dynamic linear models for multivariate time series to the functional data setting. We also develop Bayesian spline theory in a more general constrained optimization fr...