Search results for " data analysis"

A Comparison of Dyadic and Social Network Assessments of Peer Influence.

2021

The present study compares two methods for assessing peer influence: the longitudinal actor–partner interdependence model (L-APIM) and the longitudinal social network analysis (L-SNA) Model. The data were drawn from 1,995 (49% girls and 51% boys) third grade students ( Mage= 9.68 years). From this sample, L-APIM ( n = 206 indistinguishable dyads and n = 187 distinguishable dyads) and L-SNA ( n = 1,024 total network members) subsamples were created. Students completed peer nominations and objective assessments of mathematical reasoning in the spring of the third and fourth grades. Patterns of statistical significance differed across analyses. Stable distinguishable and indistinguishable L-AP…

JEM–X science analysis software

2003

The science analysis of the data from JEM-X on INTEGRAL is performed through a number of levels including corrections, good time selection, imaging and source finding, spectrum and light-curve extraction. These levels consist of individual executables and the running of the complete analysis is controlled by a script where parameters for detailed settings are introduced. The end products are FITS files with a format compatible with standard analysis packages such as XSPEC. Martinez Nuñez, Silvia, Silvia.Martinez@uv.es

A machine learning algorithm for direct detection of axion-like particle domain walls

2021

The Global Network of Optical Magnetometers for Exotic physics searches (GNOME) conducts an experimental search for certain forms of dark matter based on their spatiotemporal signatures imprinted on a global array of synchronized atomic magnetometers. The experiment described here looks for a gradient coupling of axion-like particles (ALPs) with proton spins as a signature of locally dense dark matter objects such as domain walls. In this work, stochastic optimization with machine learning is proposed for use in a search for ALP domain walls based on GNOME data. The validity and reliability of this method were verified using binary classification. The projected sensitivity of this new analy…

Functional Data Analysis with R and Matlab by RAMSAY, J. O., HOOKER, G., and GRAVES, S.

2010

The Raising Factor, That Great Unknown. A Guided Activity for Undergraduate Students

2020

In the first years of their economics degree programs, students will face many problems successfully dealing with a range of subjects with quantitative content. Specifically, in the field of statistics, difficulties to reach some basic academic achievements have been observed. Hence, a continuing challenge for statistics teachers is how to make this subject more appealing for students through the design and implementation of new teaching methodologies. The latter tend to follow two main approaches. On the one hand, it is useful for the learning process to propose practical activities that can connect theoretical concepts with real applications in the economic context. On the other hand, we …

Introducing libeemd: a program package for performing the ensemble empirical mode decomposition

2016

The ensemble empirical mode decomposition (EEMD) and its complete variant (CEEMDAN) are adaptive, noise-assisted data analysis methods that improve on the ordinary empirical mode decomposition (EMD). All these methods decompose possibly nonlinear and/or nonstationary time series data into a finite amount of components separated by instantaneous frequencies. This decomposition provides a powerful method to look into the different processes behind a given time series data, and provides a way to separate short time-scale events from a general trend. We present a free software implementation of EMD, EEMD and CEEMDAN and give an overview of the EMD methodology and the algorithms used in the deco…

Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election

2020

[EN] Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. Compared to other linear and quadratic programming models previously published, our approach presents two important innovations. Firstly, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote behaviour of young electors voting for the first time. Secondly, by exploiting the information contained in the model…

A new measure for the attitude to mobility of Italian students and graduates: a topological data analysis approach

2022

AbstractStudents’ and graduates’ mobility is an interesting topic of discussion especially for the Italian education system and universities. The main reasons for migration and for the so called brain drain, can be found in the socio-economic context and in the famous North–South divide. Measuring mobility and understanding its dynamic over time and space are not trivial tasks. Most of the studies in the related literature focus on the determinants of such phenomenon, in this paper, instead, combining tools coming from graph theory and Topological Data Analysis we propose a new measure for the attitude to mobility. Each mobility trajectory is represented by a graph and the importance of the…

Hitting Time Distributions in Financial Markets

2006

We analyze the hitting time distributions of stock price returns in different time windows, characterized by different levels of noise present in the market. The study has been performed on two sets of data from US markets. The first one is composed by daily price of 1071 stocks trade for the 12-year period 1987-1998, the second one is composed by high frequency data for 100 stocks for the 4-year period 1995-1998. We compare the probability distribution obtained by our empirical analysis with those obtained from different models for stock market evolution. Specifically by focusing on the statistical properties of the hitting times to reach a barrier or a given threshold, we compare the prob…

Thermalization of Random Motion in Weakly Confining Potentials

2010

We show that in weakly confining conservative force fields, a subclass of diffusion-type (Smoluchowski) processes, admits a family of "heavy-tailed" non-Gaussian equilibrium probability density functions (pdfs), with none or a finite number of moments. These pdfs, in the standard Gibbs-Boltzmann form, can be also inferred directly from an extremum principle, set for Shannon entropy under a constraint that the mean value of the force potential has been a priori prescribed. That enforces the corresponding Lagrange multiplier to play the role of inverse temperature. Weak confining properties of the potentials are manifested in a thermodynamical peculiarity that thermal equilibria can be approa…