Search results for "Data analysi"
showing 10 items of 391 documents
Common functional component modelling
2005
Functional data analysis (FDA) has become a popular technique in applied statistics. In particular, this methodology has received considerable attention in recent studies in empirical finance. In this talk we discuss selected topics of functional principal components analysis that are motivated by financial data.
α-decay spectroscopy of the N = 130 isotones 218Ra and 220Th: Mitigation of α-particle energy summing with implanted nuclei
2019
An analysis technique has been developed in order to mitigate energy summing due to sequential short-lived α decays from nuclei implanted into a silicon detector. Using this technique, α-decay spectroscopy of the N=130 isotones 218Ra (Z=88) and 220Th (Z=90) has been performed. The energies of the α particles emitted in the 218Ra→214Rn and 220Th→216Ra ground-state-to-ground-state decays have been measured to be 8381(4) keV and 8818(13) keV, respectively. The half-lives of the ground states of 218Ra and 220Th have been measured to be 25.99(10) μs and 10.4(4) μs, respectively. The half-lives of the ground states of the α-decay daughters, 214Rn and 216Ra, have been measured to be 259(3) ns and …
Gravitational-Wave Astronomy: Modelling, detection, and data analysis
2017
La detección directa de la primera señal de ondas gravitatorias, el 14 de Septiembre de 2015, puede considerarse uno de los mayores hitos científicos de todos los tiempos. No solo porque supone la confirmación de la última de las predicciones de la Teoría de la Relatividad General de Albert Einstein, sino porque anticipa una autentica revolución en el campo de las astrofísica, comparable a la producida con la invención del telescopio por Galileo Galilei en 1609. Este descubrimiento ha inaugurado un nuevo tipo de astronomía, la astronomía de ondas gravitatorias. Se abre así una nueva ventana al universo que permitirá el estudio de procesos físicos producidos en regiones no accesibles al espe…
$\Lambda_c^{\pm}$ production in pp collisions with a new fragmentation function
2020
Physical review / D D 101(11), 114021 (2020). doi:10.1103/PhysRevD.101.114021
Comparing proton momentum distributions in A = 2 and 3 nuclei via 2H 3H and 3He (e,e′p) measurements
2019
We report the first measurement of the $(e,e'p)$ reaction cross-section ratios for Helium-3 ($^3$He), Tritium ($^3$H), and Deuterium ($d$). The measurement covered a missing momentum range of $40 \le p_{miss} \le 550$ MeV$/c$, at large momentum transfer ($\langle Q^2 \rangle \approx 1.9$ (GeV$/c$)$^2$) and $x_B>1$, which minimized contributions from non quasi-elastic (QE) reaction mechanisms. The data is compared with plane-wave impulse approximation (PWIA) calculations using realistic spectral functions and momentum distributions. The measured and PWIA-calculated cross-section ratios for $^3$He$/d$ and $^3$H$/d$ extend to just above the typical nucleon Fermi-momentum ($k_F \approx 250$ …
Deep-learning based reconstruction of the shower maximum X max using the water-Cherenkov detectors of the Pierre Auger Observatory
2021
The atmospheric depth of the air shower maximum $X_{\mathrm{max}}$ is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of $X_{\mathrm{max}}$ are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of $X_{\mathrm{max}}$ from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of $X_{\mathrm{max}}$. The reconstruction relies on the signals induced by shower particles in the groun…
Statistical inference for eye movement sequences using spatial and spatio-temporal point processes
2017
Eye tracking is a widely used method for recording eye movements, which are important indicators of ongoing cognitive processes during the viewing of a target stimulus. Despite the variety of applications, the analyses of eye movement data have been lacking of methods that could take both the spatial and temporal information into account. So far, most of the analyses are based on strongly aggregated measures, because eye movement data are considered to be complex due to their richness and large variation between and within the individuals. Therefore, the eye movement methodology needs new statistical tools in order to take full advantage of the data. This dissertation is among the first stud…
Missing Data in Space-time: Long Gaps Imputation Based On Functional Data Analysis
2017
High dimensional data with spatio-temporal structures are of great interest in many elds of research, but their exhibited complexity leads to practical issues when formulating statistical models. Functional data analysis through smoothing methods is a proper framework for incorporating space-time structures: extending the basic methodology to the multivariate spatio-temporal setting, we refer to Generalized Additive Models for estimating functional data taking the spatial and temporal dependences into account, and to Functional Principal Component Analysis as a classical dimension reduction technique to cope with the high dimensionality and with the number of estimated eects. Since spatial …
Detecting clusters in spatially correlated waveforms
2017
Seismic networks often record signals characterized by similar shapes that provide important information according to their geographic positions. We propose an approach to identify homogeneous clusters of seismic waves, combining analysis of waveforms with metadata and spectrogram information. In waveforms clustering, cross-correlation measures between signals may presents some limitations, so we refer to more recent contributes relating data-depth based clustering analysis. The mechanism for alignment is also an important topic of the analysis: warping (or aligning) procedures identify nuisance effects in phase variation, that, if ignored, may result in a possible loss of information and t…
An Examination of Tourist Arrivals Dynamics Using Short-Term Time Series Data: A Space—Time Cluster Approach
2013
The purpose of this study is to examine the development of Italian tourist areas ( circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an…