The capacity of plants to resist abiotic stresses is of great importance to agricultural,
ecological and environmental sustainability, but little is known about its genetic …

Nowadays, due to the progress in technological advances, massive amounts of data are
generated. As a result, new statistical methodology is needed to properly manage this …

Consider a time series that takes values in a general topological space, and suppose that its
Small-ball probability is factorised into two terms that play the role of a surrogate density and …

We propose a novel method to extract global and local features of functional time series. The
global features concerning the dominant modes of variation over the entire function domain …

Functional principal component analysis (FPCA) and functional partial least squares (FPLS)
are two mainstream functional data analysis (FDA) methods, which have been commonly …

A test for proportionality of two covariance matrices with large dimension, possibly larger
than the sample size, is proposed. The test statistic is simple, computationally efficient, and …

A sizable amount of goodness-of-fit tests involving functional data have appeared in the last
decade. We provide a relatively compact revision of most of these contributions, within the …

We propose a novel test statistic for testing exogeneity in the functional linear regression
model. In contrast to Hausman-type tests in finite dimensional linear regression setups, a …

Technical development over the last few decades has resulted in the emergence of complex
data, in many cases functional data (FD). This type of data can emerge in many medical …

It's worth noting that functional data analysis greatly enriches existing data analysis
methods. It brings a broader perspective to investigate data structures. Thus, this thesis …