scholarly journals Gaussian Processes for Blazar Variability Studies

2017 ◽  
Author(s):  
Vassilis Karamanavis
Keyword(s):  
Time Series ◽  
Gaussian Processes ◽  
Light Curves ◽  
New Approach ◽  
Multi Wavelength ◽  
Wavelength Light

This article shortly introduces Gaussian processes as a new approach for modelling time series in the field of blazar physics. In the second part of the paper, recent results from an application of GP modelling to the multi-wavelength light curves of the blazar PKS 1502+106 are discussed.

scholarly journals RELATIVISTIC SHOCK ACCELERATION AND SOME CONSEQUENCES

2014 ◽  
Vol 28 ◽  
pp. 1460166 ◽  
Author(s):  
MARTIN LEMOINE ◽  
GUY PELLETIER
Keyword(s):  
Particle Acceleration ◽  
Gamma Ray ◽  
Light Curves ◽  
Shock Acceleration ◽  
Theoretical Understanding ◽  
Relativistic Shock ◽  
Multi Wavelength ◽  
The Impact ◽  
Wavelength Light ◽  
Accelerated Particles

This paper summarizes recent progresses in our theoretical understanding of particle acceleration at relativistic shock waves and it discusses two salient consequences: (1) the maximal energy of accelerated particles; (2) the impact of the shock-generated micro-turbulence on the multi-wavelength light curves of gamma-ray burst afterglows.

scholarly journals The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters

2018 ◽  
Vol 7 (2) ◽  
pp. 139-150 ◽  
Author(s):  
Adekunlé Akim Salami ◽  
Ayité Sénah Akoda Ajavon ◽  
Mawugno Koffi Kodjo ◽  
Seydou Ouedraogo ◽  
Koffi-Sa Bédja
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Time Series Data ◽  
Empirical Method ◽  
Likelihood Method ◽  
Series Data ◽  
New Approach ◽  
Weibull Parameters ◽  
Distribution Histogram ◽  
Mean Wind Speed

In this article, we introduced a new approach based on graphical method (GPM), maximum likelihood method (MLM), energy pattern factor method (EPFM), empirical method of Justus (EMJ), empirical method of Lysen (EML) and moment method (MOM) using the even or odd classes of wind speed series distribution histogram with 1 m/s as bin size to estimate the Weibull parameters. This new approach is compared on the basis of the resulting mean wind speed and its standard deviation using seven reliable statistical indicators (RPE, RMSE, MAPE, MABE, R2, RRMSE and IA). The results indicate that this new approach is adequate to estimate Weibull parameters and can outperform GPM, MLM, EPF, EMJ, EML and MOM which uses all wind speed time series data collected for one period. The study has also found a linear relationship between the Weibull parameters K and C estimated by MLM, EPFM, EMJ, EML and MOM using odd or even class wind speed time series and those obtained by applying these methods to all class (both even and odd bins) wind speed time series. Another interesting feature of this approach is the data size reduction which eventually leads to a reduced processing time.Article History: Received February 16th 2018; Received in revised form May 5th 2018; Accepted May 27th 2018; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A., Kodjo, M.K. , Ouedraogo, S. and Bédja, K. (2018) The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters. Int. Journal of Renewable Energy Development 7(2), 139-150.https://doi.org/10.14710/ijred.7.2.139-150

A new approach for optimal offline time-series segmentation with error bound guarantee

2021 ◽  
Vol 115 ◽  
pp. 107917
Author(s):  
Ángel Carmona-Poyato ◽  
Nicolás Luis Fernández-Garcia ◽  
Francisco José Madrid-Cuevas ◽  
Antonio Manuel Durán-Rosal
Keyword(s):  
Time Series ◽  
Error Bound ◽  
New Approach ◽  
Time Series Segmentation

A new approach to detect extreme events: a case study using remotely-sensed precipitation time-series data

2021 ◽  
Vol 24 ◽  
pp. 100618
Author(s):  
Philipe Riskalla Leal ◽  
Ricardo José de Paula Souza e Guimarães ◽  
Fábio Dall Cortivo ◽  
Rayana Santos Araújo Palharini ◽  
Milton Kampel
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Time Series Data ◽  
Remotely Sensed ◽  
Series Data ◽  
Precipitation Time Series ◽  
New Approach

scholarly journals An autoregressive model for irregular time series of variable stars

2016 ◽  
Vol 12 (S325) ◽  
pp. 259-262
Author(s):  
Susana Eyheramendy ◽  
Felipe Elorrieta ◽  
Wilfredo Palma
Keyword(s):  
Time Series ◽  
Gravitational Lensing ◽  
Autoregressive Model ◽  
Likelihood Estimation ◽  
Estimation Procedure ◽  
Variable Stars ◽  
Light Curves ◽  
Finite Sample ◽  
Harmonic Model ◽  
Dependency Structure

AbstractThis paper discusses an autoregressive model for the analysis of irregularly observed time series. The properties of this model are studied and a maximum likelihood estimation procedure is proposed. The finite sample performance of this estimator is assessed by Monte Carlo simulations, showing accurate estimators. We implement this model to the residuals after fitting an harmonic model to light-curves from periodic variable stars from the Optical Gravitational Lensing Experiment (OGLE) and Hipparcos surveys, showing that the model can identify time dependency structure that remains in the residuals when, for example, the period of the light-curves was not properly estimated.

scholarly journals A multi-wavelength analysis of the WASP-12 planetary system

2010 ◽  
Vol 6 (S276) ◽  
pp. 163-166 ◽  
Author(s):  
Luca Fossati ◽  
Carole A. Haswell ◽  
Cynthia S. Froning
Keyword(s):  
Magnetic Field ◽  
Atmospheric Pollution ◽  
Planetary System ◽  
Light Curves ◽  
Absorption Lines ◽  
Transiting Planets ◽  
Multi Wavelength ◽  
Global Magnetic Field ◽  
Solar Type ◽  
Solar Type Star

AbstractWASP-12 is a 2 Gyr old solar type star, hosting WASP-12b, one of the most irradiated transiting planets currently known. We observed WASP-12 in the UV with the Cosmic Origins Spectrograph (COS) on HST. The light curves we obtained in the three covered UV wavelength ranges, all of which contain many photospheric absorption lines, imply effective radii of 2.69±0.24 RJ, 2.18±0.18 RJ, and 2.66±0.22 RJ, suggesting that the planet is surrounded by an absorbing cloud which overfills the Roche lobe. We clearly detected enhanced transit depths at the wavelengths of the MgII h&k resonance lines. Spectropolarimetric analysis of the host star was also performed. We found no global magnetic field, but there were hints of atmospheric pollution, which might be connected to the very unusual activity of the host star.

scholarly journals Detecting Leaf Pulvinar Movements on NDVI Time Series of Desert Trees: A New Approach for Water Stress Detection

PLoS ONE ◽  
2014 ◽  
Vol 9 (9) ◽  
pp. e106613 ◽  
Author(s):  
Roberto O. Chávez ◽  
Jan G. P. W. Clevers ◽  
Jan Verbesselt ◽  
Paulette I. Naulin ◽  
Martin Herold
Keyword(s):  
Time Series ◽  
Water Stress ◽  
Stress Detection ◽  
New Approach ◽  
Ndvi Time Series

A NEW APPROACH OF BIVARIATE FUZZY TIME SERIES ANALYSIS TO THE FORECASTING OF A STOCK INDEX

2003 ◽  
Vol 11 (06) ◽  
pp. 671-690 ◽  
Author(s):  
YU-YUN HSU ◽  
SZE-MAN TSE ◽  
BERLIN WU
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Trading Volume ◽  
Arma Model ◽  
Future Trend ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
New Approach ◽  
Series Analysis ◽  
Closing Price

In recent years, the innovation and improvement of forecasting techniques have caught more and more attention. Especially, in the fields of financial economics, management planning and control, forecasting provides indispensable information in decision-making process. If we merely use the time series with the closing price array to build a forecasting model, a question that arises is: Can the model exhibit the real case honestly? Since, the daily closing price of a stock index is uncertain and indistinct. A decision for biased future trend may result in the danger of huge lost. Moreover, there are many factors that influence daily closing price, such as trading volume and exchange rate, and so on. In this research, we propose a new approach for a bivariate fuzzy time series analysis and forecasting through fuzzy relation equations. An empirical study on closing price and trading volume of a bivariate fuzzy time series model for Taiwan Weighted Stock Index is constructed. The performance of linguistic forecasting and the comparison with the bivariate ARMA model are also illustrated.

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