Search results for "Data Analysis"
showing 10 items of 383 documents
Functional Data Analysis and Mixed Effect Models
2004
Panel studies in econometrics as well as longitudinal studies in biomedical applications provide data from a sample of individual units where each unit is observed repeatedly over time (age, etc.). In this context, mixed effect models are often applied to analyze the behavior of a response variable in dependence of a number of covariates. In some important applications it is necessary to assume that individual effects vary over time (age, etc.).
Measuring Dissimilarity Between Curves by Means of Their Granulometric Size Distributions
2008
The choice of a dissimilarity measure between curves is a key point for clustering functional data. Functions are usually pointwise compared and, in many situations, this approach is not appropriate. Mathematical Morphology provides us with a toolbox to overcome this problem. We propose some dissimilarity measures based on morphological granulometries and their performance is evaluated on some functional datasets.
Comparing FPCA Based on Conditional Quantile Functions and FPCA Based on Conditional Mean Function
2019
In this work functional principal component analysis (FPCA) based on quantile functions is proposed as an alternative to the classical approach, based on the functional mean. Quantile regression characterizes the conditional distribution of a response variable and, in particular, some features like the tails behavior; smoothing splines have also been usefully applied to quantile regression to allow for a more flexible modelling. This framework finds application in contexts involving multiple high frequency time series, for which the functional data analysis (FDA) approach is a natural choice. Quantile regression is then extended to the estimation of functional quantiles and our proposal exp…
Functional principal component analysis for multivariate multidimensional environmental data
2015
Data with spatio-temporal structure can arise in many contexts, therefore a considerable interest in modelling these data has been generated, but the complexity of spatio-temporal models, together with the size of the dataset, results in a challenging task. The modelization is even more complex in presence of multivariate data. Since some modelling problems are more natural to think through in functional terms, even if only a finite number of observations is available, treating the data as functional can be useful (Berrendero et al. in Comput Stat Data Anal 55:2619–2634, 2011). Although in Ramsay and Silverman (Functional data analysis, 2nd edn. Springer, New York, 2005) the case of multiva…
GNSS CORS NETWORK OF THE UNIVERSITY OF PALERMO: DESIGN AND FIRST ANALYSIS OF DATA
2020
Nowadays, technical and scientific researches are focused on the use of Global Navigation Satellite System (GNSS) Continuously Operating Reference Stations (CORS) networks due to their global impact on the satellite positioning. This study aims to describe the main steps developed by the University of Palermo for the realization of the GNSS CORS network distributed in the western part of Sicily (Italy). Specifically, it focuses on data availability, preliminary studies and analyses involving the GNSS CORS network, the geodetic framework used, the coordinates and displacements time series retrieved over time and the statistical analysis with the Cumulative Distribution Function (CDF). The an…
Convergence of European regions (an approach by spatial econometrics)
2000
The aim of this paper is the analysis of spatial dependence in convergence processes applied to European regions. First, we apply the recently developed exploratory spatial data analysis (Anselin, 1996) in order to describe more precisely the geographical dynamics of European regional income growth patterns. New insights are brought to the usual cr-convergence measure, which hides geographical patterns that may fluctuate over time. Second, we test the presence of spatial autocorrelation in /^-convergence models by using spatial econometrics methods (Anselin, 1988 ; Anselin and Florax, 1995). We compare the results with and without spatial autocorrelation in order to assess the effect of geo…
Big Data in Medical Science–a Biostatistical View
2015
Big data” is a universal buzzword in business and science, referring to the retrieval and handling of ever-growing amounts of information. It can be assumed, for example, that a typical hospital generates hundreds of terabytes (1 TB = 1012 bytes) of data annually in the course of patient care (1). For instance, exome sequencing, which results in 5 gigabytes (1 GB = 109 bytes) of data per patient, is on the way to becoming routine (2). The analysis of such enormous volumes of information, i.e., organization and description of the data and the drawing of (scientifically valid) conclusions, can already hardly be accomplished with the traditional tools of computer science and statistics. For ex…
Research and Development Expenditures and Economic Growth in the EU: A Panel Data Analysis
2016
Abstract The main aim of the paper is to investigate the empirical relationship between research and development (R&D) expenditures and economic growth in the European Union member states in the period of 2000–2013. The empirical analysis is based on panel data regressions. The estimated model is the production function type standard growth model extended with R&D stock variable. The results show a statistically significant impact of R&D expenditures on the economic growth in the EU countries. The significance for R&D coefficient remains robust to different sub-periods, but the level of significance decreases as a sub-sample of new EU countries was considered.
XMM-Newton Large Program on SN1006 - I: Methods and Initial Results of Spatially-Resolved Spectroscopy
2015
Based on our newly developed methods and the XMM-Newton large program of SN1006, we extract and analyze the spectra from 3596 tessellated regions of this SNR each with 0.3-8 keV counts $>10^4$. For the first time, we map out multiple physical parameters, such as the temperature ($kT$), electron density ($n_e$), ionization parameter ($n_et$), ionization age ($t_{ion}$), metal abundances, as well as the radio-to-X-ray slope ($\alpha$) and cutoff frequency ($\nu_{cutoff}$) of the synchrotron emission. We construct probability distribution functions of $kT$ and $n_et$, and model them with several Gaussians, in order to characterize the average thermal and ionization states of such an extended s…
Searching for pulsed emission from XTE J0929-314 at high radio frequencies
2009
The aim of this work is to search for radio signals in the quiescent phase of accreting millisecond X-ray pulsars, in this way giving an ultimate proof of the recycling model, thereby unambiguously establishing that accreting millisecond X-ray pulsars are the progenitors of radio millisecond pulsars. To overcome the possible free-free absorption caused by matter surrounding accreting millisecond X-ray pulsars in their quiescence phase, we performed the observations at high frequencies. Making use of particularly precise orbital and spin parameters obtained from X-ray observations, we carried out a deep search for radio-pulsed emission from the accreting millisecond X-ray pulsar XTE J0929-31…