We provide a general class of tests for correlation in time series, spatial, spatio-temporal and cross-sectional data. We motivate our focus by reviewing how computational and theoretical difficulties of point estimation mount, as one moves from regularly-spaced time series data, through forms of ...
Universal and non-universal properties of cross-correlations in financial time series We use methods of random matrix theory to analyze the cross-correlation matrix C of price changes of the largest 1000 US stocks for the 2-year period 1994-... V Plerou,P Gopikrishnan,B Rosenow,... - ...
Time series correlations for ecology in RSean, Hardison
Stroke has emerged as a major public health concern in Malaysia. We aimed to determine the trends and temporal associations of real-time health information-seeking behaviors (HISB) and stroke incidences in Malaysia. We conducted a countrywide ecological correlation and time series study using novel...
time-seriesclusteringstatsparquet-utilscorrelations UpdatedJun 25, 2020 C# Text Mining and Analysis with Biplots. ranalysisbiplottopic-modelstextminingcorrelationssentimentsbiplots UpdatedApr 18, 2021 R A Python utility for Cramer's V Correlation Analysis for Categorical Features in Pandas Dataframes. ...
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-m... G Motta,RV Sachs,T Amemiya,... 被引量: 0发表: 2011年 Modeling Intertemporal and Contemporal Dependence in Binary TSCS Data: A Baye...
Estimating Particulate Matter-Mortality Dose-Response Curves and Threshold Levels: An Analysis of Daily Time-Series for the 20 Largest US Cities Numerous studies have shown a positive association between daily mortality and particulate air pollution, even at concentrations below regulatory limits. T......
a significant research gap remains in comprehending the varying inter-series correlations across different time scales among multiple time series, an area that has received limited attention in the literature. To bridge this gap, this paper introduces MSGNet, an advanced deep learning model designed ...
In recordings of time series, this connectivity is commonly estimated under the assumption that the sender (cause) must precede the receiver (effect) in time3. Techniques such as the Local Field Potential (LFP) and the electroencephalography (EEG), measure the postsynaptic potential of hundreds ...
CORRELATIONS IN ECONOMIC TIME SERIES 来自 EconPapers 喜欢 0 阅读量: 6 作者: Liu YH.Meyer M.Peng CK.Stanley HE.Cizeau P.摘要: A financial index of the New York stock exchange, the S&P500, is analyzed at 1 min intervals over the 13yr period, January 84-December 96. We quantify the ...