#time series analysis
10 resultsA new Granger causality measure for eliminating the confounding influence of latent common inputs
Takashi Arai
The paper introduces a Granger causality measure that reduces bias from hidden common inputs, shows its test statistic follows an F‑distribution under no interaction, and provides…
Stingray: A Modern Python Library For Spectral Timing
D. Huppenkothen, M. Bachetti, A. L. Stevens +9
Stingray is a Python library designed for spectral-timing analysis of astronomical light curves, providing Fourier analysis tools, pulsar data handling, simulation, and statistical…
A New Framework For Spatial Modeling And Synthesis of Genome Sequence
Salman Mohamadi, Farhang Yeganegi, Hamidreza Amindavar
The paper proposes a statistical framework that converts genome sequences into numeric form, separates trend and cyclic components, and models them with ARIMA‑GARCH and Gaussian mi…
Detecting individual internal displacements following a sudden-onset disaster using time series analysis of call detail records
Tracey Li, Jesper Dejby, Maximilian Albert +2
The paper introduces a method that uses mobile phone call detail records and time‑series step detection to identify individual internal displacements after sudden‑onset disasters,…
Recurrence Network Analysis of Exoplanetary Observables
Tamas Kovacs
The paper applies recurrence network methods from complex systems to both simulated and observed exoplanetary time series, showing that network measures can distinguish different d…
Inferring linear and nonlinear Interaction networks using neighborhood support vector machines
Kamel Jebreen, Badih Ghattas
The paper proposes two methods for inferring interaction networks from high‑dimensional time‑series data: a neighborhood support vector machine approach and a restricted Bayesian n…
A new method for the robust characterisation of pairwise statistical dependency between point processes
Antoine Messager, Nicos Georgiou, Luc Berthouze
The paper introduces an analytical method to robustly detect pairwise statistical dependencies between point processes, providing exact expectations, variance, and a Z‑score that r…
Is type 1 diabetes a chaotic phenomenon?
Jean-Marc Ginoux, Heikki Ruskeepää, Matjaž Perc +6
The authors analyzed minute‑by‑minute glucose measurements from ten type‑1 diabetes patients during nighttime sleep and applied nonlinear time‑series methods (delay embedding, corr…
Road Accidents in the UK (Analysis and Visualization)
Anjul Tyagi, Ayush Kumar, Anshul Gandhi +1
The paper applies Multiple Correspondence Analysis, hypothesis testing, and time‑series methods to identify and visualize key factors influencing road accidents in the UK.
Bursty time series analysis for temporal networks
Hang-Hyun Jo, Takayuki Hiraoka
The paper reviews methods for analyzing bursty temporal interaction patterns in temporal networks, describing measures such as interevent time distributions, burstiness, memory, an…