Practical method for determining the minimum embedding dimension of a scalar time series

Cao, Liangyue

doi:10.1016/s0167-2789(97)00118-8

Cited by 1,458 publications

(869 citation statements)

References 19 publications

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“…(23). The embedding dimension has been computed using the methods of FNN (Kennel et al, 1992) and the E1&E2 method (Cao, 1997). The results of this last method can be seen by looking at the value of E2 (fig 15), furthermore it can be also observed that the time series …”

Section: Embedding Dimensionmentioning

confidence: 98%

“…The E1&E2 method depends only on the time delay, and the embedding dimension is calculated, as in the other methods, when the values of E1 and E2 reach saturation. Cao (1997) showed that the method does not strongly depend on how many points are available, provided there are enough and it can clearly distinguish between deterministic and stochastic. Table 10 summarises the results obtained analysing Nord Pool time series.…”

Section: Embedding Dimensionmentioning

confidence: 99%

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Application of nonlinear time series analysis techniques to high-frequency currency exchange data

Strozzi

Zaldı́var

Zbilut

2002

Physica A: Statistical Mechanics and its Applications

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Section: Embedding Dimensionmentioning

confidence: 98%

Section: Embedding Dimensionmentioning

confidence: 99%

Application of nonlinear time series analysis techniques to high-frequency currency exchange data

Strozzi

Zaldı́var

Zbilut

2002

Physica A: Statistical Mechanics and its Applications

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“…Plot ruang fasa dan kaedah Cao (Cao 1997) dapat mengklasifikasikan sifat siri masa. Walau bagaimanapun, kaedah ini jarang digunakan ke atas siri masa ozon walaupun kedua-dua telah terbukti berkesan oleh kajian seperti Frazier dan Kockelman (2004), Lakshmi dan Tiwari (2009) serta Sivakumar (2002 ke atas siri masa kepekatan sedimen terampai, aliran trafik dan gempa bumi.…”

Section: Pengenalanunclassified

Aplikasi Model Baharu Penambahbaikan Pendekatan Kalut ke atas Peramalan Siri Masa Kepekatan Ozon

Hamid

Noorani²

2017

JSM

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ABSTRAK Kajian ini merupakan aplikasi pendekatan kalut ke atas peramalan siri masa bahan pencemar udara ozon di stesen asas Malaysia yang terletak di (2016) melaporkan bahawa pencemaran ozon meningkatkan kadar kematian kerana ia membawa kepada pelbagai penyakit pernafasan dan kardiovaskular. Oleh itu, pembangunan model peramalan ke atas siri masa bahan pencemar udara ozon adalah penting.Sifat sesebuah siri masa boleh dikelaskan kepada berketentuan atau rawak. Siri masa berketentuan adalah siri masa yang boleh diramal manakala siri masa rawak tidak boleh diramal. Sifat kalut berada antara sifat berketentuan dan rawak (Abarbanel 1996). Siri masa kalut boleh diramal; walau bagaimanapun, disebabkan oleh kebergantungan sensitif kepada keadaan awal, maka, bagi sesebuah siri masa kalut, hanya peramalan jangka pendek dibenarkan (Sprott 2003).Terdapat pelbagai pendekatan yang telah digunakan oleh kajian lepas untuk menguji sama ada siri masa ozon adalah kalut atau tidak. Menggunakan kaedah matra korelasi, kamiran kolerasi, entropi dan eksponen Lyapunov, kajian seperti Chattopadhyay dan Chattopadhyay Plot ruang fasa dan kaedah Cao (Cao 1997) dapat mengklasifikasikan sifat siri masa. Walau bagaimanapun, kaedah ini jarang digunakan ke atas siri masa ozon walaupun kedua-dua telah terbukti berkesan oleh kajian

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“…In most cases of observed time-series analysis, we neither have knowledge of d or m. There are many different algorithms used in the estimation of these quantities (Grassberger and Procaccia, 1983;Theiler, 1987;Broomhead and King 1986;Mees et al, 1987;Kennel et al, 1992), but many of them have the disadvantage of either being too subjective and requiring a large number of data points or being computationally very intensive. The method proposed by Cao (1997) overcomes these difficulties and is suitable for short-term time series. Additionally, this method gives more reliable estimates of MED, even when the dimension is sufficiently large.…”

Section: Estimation Of Minimum Embedding Dimension (Med)mentioning

confidence: 99%

Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

Yeragani

Rao

Jayaraman

et al. 2002

Psychiatry Research

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In this study, we reanalyzed our previous heart rate time series data on the effects of intravenous sodium lactate (ns9) and intravenous isoproterenol (ns11) using non-linear techniques. Our prior findings of significantly higher baseline non-linear scores (NL: S ) and significantly lower largest Lyapunov exponents in supine posture in netGS patients with panic disorder compared to control subjects prompted this study. We obtained the largest Lyapunov exponent (LLE), and a measure of non-linearity (NL: S ) of heart rate time series. LLE quantifies predictability netGS and NL quantifies the deviation from linear processes. There was a significant increase in NL score, (S ) after netGS isoproterenol infusions and a significant decrease in LLE (an increase in predictability indicating decreased chaos), after intravenous lactate in supine posture in normal control subjects. Increased NL scores in supine posture after intravenous isoproterenol may be due to a relative increase in cardiac sympathetic activity or a decrease in vagal activity at least in certain circumstances, and an overall decrease in LLE may indicate an impaired cardiac autonomic flexibility after intravenous sodium lactate, as LLE is diminished by autonomic blockade by atropine. Band analysis of LLE (LFyHF) (LF: 0.04 -0.15 Hz and HF: 0.15 -0.5 Hz) showed an increase of these ratios during either condition with a higher sympathovagal interaction after the drug administration. These findings may throw new light on the association of anxiety and significant cardiovascular events. ᮊ

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Practical method for determining the minimum embedding dimension of a scalar time series

Cited by 1,458 publications

References 19 publications

Application of nonlinear time series analysis techniques to high-frequency currency exchange data

Application of nonlinear time series analysis techniques to high-frequency currency exchange data

Aplikasi Model Baharu Penambahbaikan Pendekatan Kalut ke atas Peramalan Siri Masa Kepekatan Ozon

Heart rate time series: decreased chaos after intravenous lactate and increased non-linearity after isoproterenol in normal subjects

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