Multivariate Time Series Similarity Searching by Jimin Wang, Yuelong Zhu, Shijin Li, Dingsheng Wan, Pengcheng Zhang

“…Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. …”
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Implementation of bagging in time series forecasting by Ia. V. Gramovich, D. Yu. Musatov, D. A. Petrusevich

“…The purpose of the article is to build different models of bagging, to compare the accuracy of their forecasts for the test period against standard models, and to draw conclusions about the possibility of further use of the bagging technique in time series modeling.Methods. This study examines the application of bagging to the random component of a time series formed after removing the trend and seasonal part. …”
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Disentangling Sources of Multifractality in Time Series by Robert Kluszczyński, Stanisław Drożdż, Jarosław Kwapień, Tomasz Stanisz, Marcin Wątorek

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Coping with Nonstationarity in Categorical Time Series by Monnie McGee, Ian Harris

“…Categorical time series are time-sequenced data in which the values at each time point are categories rather than measurements. …”
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G-Filtering Nonstationary Time Series by Mengyuan Xu, Krista B. Cohlmia, Wayne A. Woodward, Henry L. Gray

“…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. …”
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Time series aggregation, disaggregation and long memory by Dmitrij Celov, Remigijus Leipus

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A Review of Subsequence Time Series Clustering by Seyedjamal Zolhavarieh, Saeed Aghabozorgi, Ying Wah Teh

“…Clustering of subsequence time series remains an open issue in time series clustering. …”
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Spatial time-series modeling with R system by Laura Šaltytė, Kęstutis Dučinskas

Subjects: “…spatial time series modeling…”
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Statistical analysis of time series with scaling indices by Harald Atmnaspacher, Werner Ehm, Herbert Scheingraber, Gerda Wiedenmann

Subjects: “…Time series analysis; Pattern detection; Scaling indices.…”
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Conversion of 10 min Rain Rate Time Series into 1 min Time Series: Theory, Experimental Results, and Application in Satellite Communications by Emilio Matricciani, Carlo Riva

“…We propose a semi-empirical method—based on a filtered Markov process—to convert 10 min rain rate time series into 1 min time series, i.e., quasi-instantaneous rainfall—the latter to be used as input to the synthetic storm technique, which is a very reliable tool for calculating rain attenuation time series in satellite communication systems or for estimating runoff, erosion, pollutant transport, and other applications in hydrology. …”
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Chaotic Dynamics Analysis Based on Financial Time Series by Zheng Gu, Yuhua Xu

“…In this paper, the chaotic dynamic properties of financial time series are analyzed. Firstly, the nonlinear characteristics of the data are discussed through the empirical analysis of agriculture index data; the daily agriculture index returns can be decomposed into the different scales based on wavelet analysis. …”
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Accuracy analysis of different components evaluation of time series by Vitalija Klokova

“… Mathematical models for decomposing and forecasting of time series are analysed in this paper. Sometimes we have the situations when we don't get good result describing time series by standard components (trend, cyclical, seasonal). …”
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Stability Conditions for a Nonlinear Time Series Model by Anas S. Youns, Salim M. Ahmad

“…This research aims to determine whether the proposed time series model is stable or not. To achieve this, Ozaki’s approximation method was utilized, where the nonlinear part is a function that approaches zero, similar to Ozaki’s imposed function. …”
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Growth-rate distributions of gut microbiota time series by E. Brigatti, S. Azaele

“…The simulated processes generated by the calibrated stochastic equation and the analysis of each time-series, taken one by one, provided additional support for our approach. …”
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Testing financial time series for autocorrelation: Robust Tests by Nelson Omar Muriel Torrero

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Compound Autoregressive Network for Prediction of Multivariate Time Series by Yuting Bai, Xuebo Jin, Xiaoyi Wang, Tingli Su, Jianlei Kong, Yutian Lu

“…There are obvious nonlinear, nonstationary, and complicated characteristics in the time series. Moreover, multiple variables in the time-series impact on each other to make the prediction more difficult. …”
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Multidimensional time series classification with multiple attention mechanism by Chen Liu, Zihan Wei, Lixin Zhou, Ying Shao

Subjects: “…Multidimensional time series…”
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Fractal Characteristic of Rock Cutting Load Time Series by Hongxiang Jiang, Changlong Du, Songyong Liu, Kuidong Gao

“…The fractal theory was adopted to investigate the fractal characteristic of cutting load time series and fragment size distribution in rock cutting. …”
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Test for Change in Error Variance of Multiple Time Series by Elfred John C. Abacan, Joseph Ryan G. Lansangan, Erniel B. Barrios

“…Volatility structures may incorporate variance into the time series models, but these can easily lead to overparameterization in multiple time series. …”
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Mixed Portmanteau Test for Diagnostic Checking of Time Series Models by Sohail Chand, Shahid Kamal

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