Results 131 to 140 of about 7,132,026 (272)

A partial envelope approach for modelling multivariate spatial‐temporal data

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja   +3 more
wiley   +1 more source

The Scaling Limit of Random Two-Connected Series-Parallel Maps. [PDF]

open access: yesJ Theor Probab
Amankwah D   +4 more
europepmc   +1 more source

Copula‐based joint modelling of emergency department visits with time‐varying dependence

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source

Stochastic thermodynamics of social imitation beyond energetics. [PDF]

open access: yesNat Commun
Irisarri L   +3 more
europepmc   +1 more source

The Shorth Plot [PDF]

open access: yes
The shorth plot is a tool to investigate probability mass concentration. It is a graphical representation of the length of the shorth, the shortest interval covering a certain fraction of the distribution, localized by forcing the intervals considered to
Gantner, M.   +2 more
core  

Power spectral density and the brain

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Time series from M/EEG (magneto/electroencephalography) and ECoG (electrocorticography) recordings are common sources of information about brain function. The power spectral density (PSD) preserves much of this information, up to second order. In the current decade, a burst of brain diagnostics using the slope of log(PSD) has appeared.
Priscilla E. Greenwood   +2 more
wiley   +1 more source

Nonparametric maximum likelihood estimation of the survival function using current lifetime data

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract An issue when estimating the failure time survival function is how to set up a prevalent cohort study infrastructure to follow subjects after enrollment. This problem can be circumvented through the well‐known Grenander density estimator using current lifetime observations only.
James H. McVittie, Masoud Asgharian
wiley   +1 more source

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