Causality Detection Methods Applied to the Investigation of Malaria Epidemics

Murari, A.; Gelfusa, M.

doi:10.3390/e21080784

Cited by 12 publications

(4 citation statements)

References 49 publications

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“…These results might be stem from the phenomenon that we have not considered or the limitation of causal decomposition itself. Some previous studies also exhibited less obvious and unclear direction of the causality or sometimes contradictory results in interpreting the causal decomposition results [30] , [31] . The energy strength of IMFs and their causal strength varies from different factors, and the causality results might differ in severe fluctuation among different frequency domains.…”

Section: Empirical Analysismentioning

confidence: 93%

“…On the other hand, causal decomposition has the advantage of reflecting real-world data and phenomena based on instantaneous phase dependency between cause and effect, that is, oscillatory stochastic and deterministic mechanisms [7] . Several studies applied this technique to the change rate for the GDP time series between major on a different time scale [30] and the investigation of Malaria epidemics [31] .…”

Section: Literature Reviewmentioning

confidence: 99%

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Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition

Cho¹,

Kim²,

Kim³

2022

Physica A: Statistical Mechanics and its Applications

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Section: Empirical Analysismentioning

confidence: 93%

Section: Literature Reviewmentioning

confidence: 99%

Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition

Cho¹,

Kim²,

Kim³

2022

Physica A: Statistical Mechanics and its Applications

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“…As shown in [ 15 , 40 ], WAM can be represented as an image and used for monitoring the complexity of the network, which is linked to the degree of coupling between time series. The image entropy

can be used to evaluate the complexity of the WAM image.…”

Section: Image Representation Of Time Seriesmentioning

confidence: 99%

Image-Based Methods to Investigate Synchronization between Time Series Relevant for Plasma Fusion Diagnostics

Murari

Lerche

Gelfusa

et al. 2020

Entropy

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Advanced time series analysis and causality detection techniques have been successfully applied to the assessment of synchronization experiments in tokamaks, such as Edge Localized Modes (ELMs) and sawtooth pacing. Lag synchronization is a typical strategy for fusion plasma instability control by pace-making techniques. The major difficulty, in evaluating the efficiency of the pacing methods, is the coexistence of the causal effects with the periodic or quasi-periodic nature of the plasma instabilities. In the present work, a set of methods based on the image representation of time series, are investigated as tools for evaluating the efficiency of the pace-making techniques. The main options rely on the Gramian Angular Field (GAF), the Markov Transition Field (MTF), previously used for time series classification, and the Chaos Game Representation (CGR), employed for the visualization of large collections of long time series. The paper proposes an original variation of the Markov Transition Matrix, defined for a couple of time series. Additionally, a recently proposed method, based on the mapping of time series as cross-visibility networks and their representation as images, is included in this study. The performances of the method are evaluated on synthetic data and applied to JET measurements.

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“…Over the past few years, Granger Causality (GC) (Granger, 1969) has been commonly used to detect the causality between variables, where X is considered to be the Granger cause of Y if the predictability of Y declines when removing X from all possible causative variables (Craciunescu et al, 2019). The algorithm implies at least two preconditions that limit the use of GC: (1) Causes must occur before effects; and (2) causes can be separated from effects.…”

Section: Introductionmentioning

confidence: 99%

Multifaceted characteristics of aridity changes and causal mechanisms in Chinese drylands

Wei

et al. 2022

Progress in Physical Geography: Earth and Environment

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The water cycle is accelerating in the context of global warming. However, how the multifaceted characteristics of aridity, particularly atmospheric, hydrological, and ecological drying, change and interact with each other are largely unknown. A gap we bridged was discovering the causal relationships underlying the atmosphere-hydrosphere-biosphere nexus from the nonlinear dynamic system perspective based on convergent cross mapping (CCM). Dryland area in China has expanded since 1982, while the vegetation greenness indicated by leaf area index has been increasing during the same period. The results showed that the causality among atmospheric, hydrological, and ecological drying in different subtypes of drylands was different. In arid and semi-arid regions: vegetation changes were mainly driven by soil moisture (SM) and vapor pressure deficit (VPD), and VPD regulated SM. In hyper-arid and dry sub-humid areas: VPD dominated vegetation changes. VPD increases did not contribute to SM loss under the intense water stress in hyper-arid regions, as the soil water supply cannot meet the atmospheric water demand. In dry sub-humid areas, human disturbances have attenuated the dependence of vegetation changes on SM variability. This research pioneers complex nonlinear dynamic analyses on the multifaceted characteristics of ecosystems, which can deepen our understanding of atmosphere-vegetation-soil interactions in drylands and guide the sustainable management of dryland ecosystems in China and elsewhere.

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Causality Detection Methods Applied to the Investigation of Malaria Epidemics

Cited by 12 publications

References 49 publications

Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition

Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition

Image-Based Methods to Investigate Synchronization between Time Series Relevant for Plasma Fusion Diagnostics

Multifaceted characteristics of aridity changes and causal mechanisms in Chinese drylands

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