Results 151 to 160 of about 4,545 (215)
Residual XGBoost regression-Based individual moving range control chart for Gross Domestic Product growth monitoring. [PDF]
PLoS OneAisy RR, Zulfa L, Rahim Y, Ahsan M.
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The relationship between virulence and drug resistance genes in <i>Pseudomonas aeruginosa</i> and antibiotic resistance: a targeted next-generation sequencing approach. [PDF]
Front Cell Infect MicrobiolWei H +7 more
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Effects of Scutellaria baicalensis, Folium Artemisiae argyi, and Galla Chinensis on the protein expression and resistance genes of Exiguobacterium sp. in response to gentamicin. [PDF]
Sci RepWang X +5 more
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Forecasting Tuberculosis Incidence in Somalia: A Comparative Analysis of Single and Hybrid Time-Series Models. [PDF]
Health Sci RepDahir HM +4 more
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Mind the Baseline: The Hidden Impact of Reference Model Selection on Forecast Assessment
Stapper M, Funk S.
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2022
AbstractChapter 5 enters into stochastic time series analysis with the description of moving average, autoregressive and autoregressive moving average processes. Seasonal time series analysis is introduced with examples applied to measures temperature and the hydrological cycle.
Marco Bittelli +2 more
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AbstractChapter 5 enters into stochastic time series analysis with the description of moving average, autoregressive and autoregressive moving average processes. Seasonal time series analysis is introduced with examples applied to measures temperature and the hydrological cycle.
Marco Bittelli +2 more
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IEEE Transactions on Signal Processing, 1994
Parametric modeling of multichannel time series is accomplished by using higher (than second) order statistics (HOS) of the observed nonGaussian data. Cumulants of vector processes are defined using a Kronecker product formulation, and consistency of their sample estimators is addressed.
A. Swami, G. Giannakis, S. Shamsunder
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Parametric modeling of multichannel time series is accomplished by using higher (than second) order statistics (HOS) of the observed nonGaussian data. Cumulants of vector processes are defined using a Kronecker product formulation, and consistency of their sample estimators is addressed.
A. Swami, G. Giannakis, S. Shamsunder
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INFINITE VARIANCE STABLE ARMA PROCESSES
Journal of Time Series Analysis, 1994Abstract. The asymptotic dependence structure of autoregressive moving‐average processes with stable innovations is analyzed. The analysis is carried out by means of a measure of dependence which extends the covariance function and is applicable to stochastic processes with infinite variance.
Kokoszka, Piotr S., Taqqu, Murad S.
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