Results 71 to 80 of about 7,569,463 (308)
Using Dynamics to Analyse Time Series
, 2017 We present a review of recent work to analyze time series in a robust manner using Wasserstein distances which are numerical costs of an optimal transportation problem. Given a time series, the long-term behavior of the dynamical system represented by the time series is reconstructed by Takens delay embedding method.
openaire +2 more sources
Molecular Oncology, EarlyView.Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach +9 more
wiley +1 more source
Dynamic parameters for Brazilian financial time series
Economia Aplicada, 2002 In this study we analyse a Brazilian stock index called IBOVESPA using techniques from dynamical systems theory and stochastic processes. We discuss the Lyapunov exponent, the correlation dimension, the LempelZiv complexity, the Hurst exponent and the ...
Gerson Francisco +2 more
doaj
Fitting dynamic factor models to non-stationary time series [PDF]
Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some ...
Eichler Michael +2 more
core
CEACAM1 participation in breast cancer progression
Molecular Oncology, EarlyView.In invasive breast cancer (BC), CEACAM1 shifts from an apical to a uniform membranous/cytoplasmic pattern, or is lost, as tumors dedifferentiate, inversely tracking the Ki‐67 proliferative index. In MCF‐7 cells, only CEACAM1‐4L suppresses proliferation, repressing cell cycle and growth factor genes.
Mykola Lyndin +3 more
wiley +1 more source
Nonparametric time series forecasting with dynamic updating [PDF]
We present a nonparametric method to forecast a seasonal univariate time series, and propose four dynamic updating methods to improve point forecast accuracy. Our methods consider a seasonal univariate time series as a functional time series.
Han Lin Shang, Rob J Hyndman
core
Pharmacological chromatin remodeling enhances response to estrogen therapy in ER+ breast cancer
Molecular Oncology, EarlyView.Estrogen therapy elicits clinical benefit in ~ 30% of patients with endocrine‐resistant estrogen receptor (ER)‐positive breast cancer. Based on findings that ER transcriptional activation underlies response to estrogen therapy, we tested the effects of epigenetic dysregulation via pharmacological inhibition of histone deacetylases (HDACi).
Anneka L. Johnson Thomas +16 more
wiley +1 more source
Fuzzy Dynamic Reliability Model of Dependent Series Mechanical Systems
Advances in Mechanical Engineering, 2013 Conventional static fuzzy reliability models cannot be directly extended for dynamic reliability analysis of mechanical systems, which consist of correlative components with strength degradation, due to the difficulties in describing the strength ...
Peng Gao, Shaoze Yan
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Molecular Oncology, EarlyView.Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche +10 more
wiley +1 more source
Estimation of Dynamic Networks for High-Dimensional Nonstationary Time Series
Entropy, 2019 This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes.
Mengyu Xu, Xiaohui Chen, Wei Biao Wu
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