Exploratory joint and separate tracking of geographically related time series

2012 ◽  
Author(s):  
Balakumar Balasingam ◽  
Peter Willett ◽  
Georgiy Levchuk ◽  
Jared Freeman
Keyword(s):  
Time Series ◽  
Related Time Series

Data Imputation in Related Time Series Using Fuzzy Set-Based Techniques

2020 ◽  
Author(s):  
Adam Kiersztyn ◽  
Pawel Karczmarek ◽  
Rafal Lopucki ◽  
Witold Pedrycz ◽  
Ebru Al ◽  
...  
Keyword(s):  
Time Series ◽  
Fuzzy Set ◽  
Data Imputation ◽  
Related Time Series

Multi-Fractal Nature of HS 300 Index and its Traded Volume

2012 ◽  
Vol 629 ◽  
pp. 796-800
Author(s):  
Shun Gen Zuo
Keyword(s):  
Time Series ◽  
Spectrum Analysis ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Fractal Nature ◽  
Fractal Spectrum ◽  
Detrended Fluctuation ◽  
Related Time Series

A study of the multi-fractal nature of three time series related to the Hushen300 index, HS300, including daily closing prices, daily yield rates and daily traded volumes time series is presented. Multi-fractal Detrended Fluctuation Analysis (MFDFA) is used in the study. The results show that the three related time series are with strong persistence characters. By multi-fractal spectrum analysis, the width of the multi-fractal Spectra of traded volume series is to be found the biggest among the three. It means that the traded volumes series are most irregular.

scholarly journals General Quantile Time Series Regressions for Applications in Population Demographics

Risks ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 97 ◽  
Author(s):  
Gareth Peters
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Data Sets ◽  
Population Demographics ◽  
General Audience ◽  
Times Series ◽  
Morbidity Data ◽  
Core Components ◽  
Related Time Series

The paper addresses three objectives: the first is a presentation and overview of some important developments in quantile times series approaches relevant to demographic applications—secondly, development of a general framework to represent quantile regression models in a unifying manner, which can further enhance practical extensions and assist in formation of connections between existing models for practitioners. In this regard, the core theme of the paper is to provide perspectives to a general audience of core components that go into construction of a quantile time series model. The third objective is to compare and discuss the application of the different quantile time series models on several sets of interesting demographic and mortality related time series data sets. This has relevance to life insurance analysis and the resulting exploration undertaken includes applications in mortality, fertility, births and morbidity data for several countries, with a more detailed analysis of regional data in England, Wales and Scotland.

scholarly journals Analysis of Rattleback Chaotic Oscillations

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Michael Hanias ◽  
Stavros G. Stavrinides ◽  
Santo Banerjee
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Chaotic Dynamics ◽  
The Other ◽  
Strange Attractors ◽  
Rotational Behaviour ◽  
Chaotic Oscillations ◽  
Kinematic Behaviour ◽  
Ancient Times ◽  
Related Time Series

Rattleback is a canoe-shaped object, already known from ancient times, exhibiting a nontrivial rotational behaviour. Although its shape looks symmetric, its kinematic behaviour seems to be asymmetric. When spun in one direction it normally rotates, but when it is spun in the other direction it stops rotating and oscillates until it finally starts rotating in the other direction. It has already been reported that those oscillations demonstrate chaotic characteristics. In this paper, rattleback’s chaotic dynamics are studied by applying Kane’s model for different sets of (experimentally decided) parameters, which correspond to three different experimental prototypes made of wax, gypsum, and lead-solder. The emerging chaotic behaviour in all three cases has been studied and evaluated by the related time-series analysis and the calculation of the strange attractors’ invariant parameters.

An Approximation to Deep Learning Touristic-Related Time Series Forecasting

2018 ◽  
pp. 448-456
Author(s):  
Daniel Trujillo Viedma ◽  
Antonio Jesús Rivera Rivas ◽  
Francisco Charte Ojeda ◽  
María José del Jesus Díaz
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Forecasting ◽  
Related Time Series

scholarly journals Dynamically Consistent Noise Infusion and Partially Synthetic Data as Confidentiality Protection Measures for Related Time Series

2012 ◽  
Author(s):  
John M. Abowd ◽  
R. Kaj Gittings ◽  
Kevin McKinney ◽  
Bryce Stephens ◽  
Lars Vilhuber ◽  
...  
Keyword(s):  
Time Series ◽  
Synthetic Data ◽  
Protection Measures ◽  
Related Time Series ◽  
Confidentiality Protection
Sign in / Sign up

Export Citation Format

Share Document