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In a single equation time series framework, it is possible to study the effect of a shock contemporaneous or time dependent in an exogenous variable, using intervention or transfer function analysis, respectively.
The use of a time series framework, in this research, directly addresses this issue.
3 This research directly addresses this issue by adopting a time series framework.
In this analysis, we use C&RT to identify multipollutant mixtures associated with pediatric asthma emergency department (ED) visits and calculate the joint effects associated with each mixture in a time series framework.
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This line of thinking suggests that a time series model in the GLM framework may be better at describing GDV occurrence than the regular logistic GLM model considered in [ 7].
The studied latent time-series framework not only covers classical ARMA type models and their fractionally integrated generalizations, i.e., autoregressive fractionally integrated moving average (ARFIMA) processes but also allows for inference of time-series with heterogeneous memory properties.
In this communication, a new grey fuzzy Markov time series model, developed from nondifferential grey interval analytical framework has been presented for the first time.
With the help of developed time series segmentation framework, separation of operation regimes becomes possible for supporting process monitoring and control.
This assessment is usually based on a time series design, a framework which has gained a substantial development in the last two decades.
FMRI data were analyzed using voxel-wise time series analysis within the framework of the General Linear Model (GLM).
Out of several possible modeling approaches, this research used the one that is based on putting integer valued time series in the generalized linear model framework [ 13].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com