Results 1 to 10 of about 9,928,788 (281)

Modelling Time Series Extremes

Revstat Statistical Journal, 2012
The need to model rare events of univariate time series has led to many recent advances in theory and methods. In this paper, we review telegraphically the literature on extremes of dependent time series and list some remaining challenges.
V. Chavez-Demoulin , A.C. Davison
doaj   +1 more source

Independence Testing for Multivariate Time Series

, 2020
Complex data structures such as time series are increasingly present in modern data science problems. A fundamental question is whether two such time-series are statistically dependent.
Chung, Jaewon, Mehta, Ronak, Shen, Cencheng, Vogelstein, Joshua T., Xu, Ting   +4 more
core  

Periodicity in wide-band time series [PDF]

, 2002
Summary: To test the hypotheses that (i) electroencephalograms (EEGs) are largely made up of oscillations at many frequencies and (ii) that the peaks in the power spectra represent oscillations, we applied a new method, called the Period Specific ...
Bullock, T.H., Enright, J.T., McClune, M.C.   +2 more
core  

Peramalan Data Kunjungan Wisatawan Mancanegara ke Indonesia menggunakan Fuzzy Time Series

JEPIN (Jurnal Edukasi dan Penelitian Informatika), 2019
Wisatawan mancanegara memegang peranan penting terhadap pertumbuhan ekonomi dari sektor pariwisata. Untuk meningkatkan kunjungan wisatawan mancanegara perlu dilakukan pembangunan yang berkelanjutan pada sektor pariwisata. Pembangunan yang dilakukan harus
Indra Jiwana Thira, Nissa Almira Mayangky, Desiana Nur Kholifah, Imanuel Balla, Windu Gata   +4 more
doaj   +1 more source

Finding Motif Sets in Time Series [PDF]

, 2014
Time-series motifs are representative subsequences that occur frequently in a time series; a motif set is the set of subsequences deemed to be instances of a given motif. We focus on finding motif sets. Our motivation is to detect motif sets in household
Bagnall, Anthony, Hills, Jon, Lines, Jason   +2 more
core   +1 more source

G-Filtering Nonstationary Time Series

Journal of Probability and Statistics, 2012
The classical linear filter can successfully filter the components from a time series for which the frequency content does not change with time, and those nonstationary time series with time-varying frequency (TVF) components that do not overlap. However,
Mengyuan Xu, Krista B. Cohlmia, Wayne A. Woodward, Henry L. Gray   +3 more
doaj   +1 more source

Temperature time-series? [PDF]

Nature, 1992
Allen, M, Read, P, Smith, L
openaire   +1 more source

Modelling bursty time series

New Journal of Physics, 2013
Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty time series due to the non-trivial dynamics of the task list ...
Szabolcs Vajna, Bálint Tóth, János Kertész   +2 more
doaj   +1 more source

Modeling Seasonal Time Series [PDF]

Surveys in Mathematics and its Applications, 2006
The paper studies the seasonal time series as elements of a (finite dimensional) Hilbert space and proves that it is always better to consider a trend together with a seasonal component even the time series seams not to has one.
Alexandra Colojoara
doaj  

Eigen-entropy based time series signatures to support multivariate time series classification

Scientific Reports
Most current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative moving window ...
Abhidnya Patharkar, Jiajing Huang, Teresa Wu, Erica Forzani, Leslie Thomas, Marylaura Lind, Naomi Gades   +6 more
doaj   +1 more source