Search results for "Principal components"

Functional principal component analysis as a new methodology for the analysis of the impact of two rehabilitation protocols in functional recovery af…

2014

[EN] Background: This study addressed the problem of evaluating the effectiveness of two protocols of physiotherapy for functional recovery after stroke. In particular, the study explored the use of Functional Principal Component Analysis (FPCA), a multivariate data analysis in order to assess and clarify the process of regaining independence after stroke. Methods: A randomized double-blind controlled trial was performed. Thirteen subjects with residual hemiparesis after a single stroke episode were measured in both in- and outpatient settings at a district hospital. All subjects were able to walk before suffering the stroke and were hemodynamically stable within the first week after stroke…

A new genus and species of asteraceae-inhabiting aphid (hemiptera: aphididae) from Costa Rica and Mexico

2013

P. 323-331 Ucrimyzus villalobosi Mier Durante & Pérez Hidalgo gen. n., sp. n. (Hemiptera: Aphididae: Macrosiphini) are described from apterous and alate viviparous females collected on species of genera Bidens, Schkuhria, Senecio and Stevia (Asteraceae: Asteroideae) in Costa Rica and Mexico. Principal components analysis (PCA) was done to verify that the studied aphids belong to a single species regardless of their geographical origin or host plant. Molecular analyses were carried out on the sequences of a fragment of the mitochondrial gene encoding for cytochrome c oxidase subunit 1 (COI) and of a fragment of the nuclear gene encoding elongation factor 1α (EF1α). The taxonomic discussion t…

Impact of Global Economic Crisis on the European Welfare States

2013

The global economic crisis and the subsequent weaker growth are putting under pressure welfare states in the EU. This paper aims at discussing the effects of the crisis at the social level and at identifying whether the classic European welfare state models (Nordic, Continental, Anglo-Saxon and Mediterranean) are still valid in today’s economy. An answer will be tried using the mathematical tool of principal components analysis. The results will be observed in graphs where the states taken into consideration respect the classical welfare models or they regroup themselves into new circumstances’ adapted models. Even though the classical welfare models are generally still checked up with the …

Multivariate Methods and Molecular Modeling Techniques in the study of Antitumor Agents

2008

The Global Side of the Investments-Savings Puzzle

2008

In this paper we re-examine the long standing and puzzling correlation between national savings and investment in industrial countries. We apply an econometric methodology that allows us to separate idiosyncratic correlation at the country level from correlation at the global level. In a major break with the existing literature, we find no evidence of a long run relationship in the idiosyncratic components of savings and investment. We also find that the global components in savings and investments commove, indicating that they react to shocks of a global nature.

The affine equivariant sign covariance matrix: asymptotic behavior and efficiencies

2003

We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Statist. Plann. Inference 91 (2000) 557). The population SCM is shown to be proportional to the inverse of the regular covariance matrix. The eigenvectors and standardized eigenvalues of the covariance, matrix can thus be derived from the SCM. We also construct an estimate of the covariance and correlation matrix based on the SCM. The influence functions and limiting distributions of the SCM and its eigenvectors and eigenvalues are found. Limiting efficiencies are given in multivariate normal and t-distribution cases. The estimates are highly efficient in the multivariate normal case and perform …

Functional principal component analysis of quantile curves

2017

Literature on functional data analysis is mainly focused on estimation of individuals curves and characterization of average dynamics. The idea underlying this proposal is to focus attention on other particular features of the distribution of the observed data, moving from mean functions towards functional quantiles. The motivating examples are functional data sets that are collections of high frequency data recorded along time. As quantiles provide information on various aspects of a time series, we propose a modelling framework for the joint estimation of functional quantiles, varying along time, and functional principal components, summarizing some common dynamics shared by the functiona…