Search results for "Data Analysi"
showing 10 items of 391 documents
A functional approach to monitor and recognize patterns of daily traffic profiles
2014
Functional Data Analysis (FDA) is a collection of statistical techniques for the analysis of information on curves or functions. This paper presents a new methodology for analyzing the daily traffic flow profiles based on the employment of FDA. A daily traffic profile corresponds to a single datum rather than a large set of traffic counts. This insight provides ideal information for strategic decision-making regarding road expansion, control, and other long-term decisions. Using Functional Principal Component Analysis the data are projected into a low dimensional space: the space of the first functional principal components. Each curve is represented by their vector of scores on this basis.…
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…
Identification and modeling of stop activities at the destination from GPS tracking data
2021
Il presente articolo ha lo scopo di analizzare il comportamento turistico a destinazione, con un focus specifico sulle soste effettuate dai turisti nella destinazione. Vengono analizzati dati desunti da dispositivi GPS raccolti su un campione di crocieristi, a partire dai quali e possibile individuare le soste a destinazione `attraverso l’impiego di un opportuno algoritmo. L’effetto delle caratteristiche sociodemografiche e legate all’itinerario intrapreso sul numero di soste effettuate viene studiato attraverso l’impiego di modelli di reggressione di Poisson. I risultati sono di interesse sia da un punto di vista metodologico, legato all’analisi e sintesi di dati GPS, che dal punto di vist…
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.