model averaging, by which estimates are obtained based on not one single model but a weighted ensemble of models, has received growing attention as an alternative to model selection. To-date, methods for model averaging have been developed almost exclusively for point-valued data, despite the fact...
Model averaging for interval-valued dataYuying Sun a b cXinyu Zhang a b dAlan T.K. Wan eShouyang Wang a b c
We drew our training set for the autoencoder from the cAb-Rep database41, which contains sequenced B-cell receptor repertoires for 121 human donors representing true antibody sequences. Specifically, we filtered the high-depth repertoire dataset using the ANARCI software package42(see “Methods” f...
Posterior predictive checks, comparing simulation-based inference (SBI) of the spectral graph model (SGM) derived spectral realizations to observed data, are shown for three representative subject EEGsa,c,e. Observed EEG spectra are demonstrated ina,c,e(black traces), and their respective approximate...
The hybrid SF-entropy measure-RS-RAFSI framework for assessing adoption barriers to DT has three stages. In the first stage, the SF-WHMA operator with entropy measure is used to collect the experts' preference information, considering the relationship among these input data. In the second stage...
Neuronal adaptation as well as interdischarge interval correlations have been shown to be functionally important properties of physiological neurons. We explore the dynamics of a modified leaky integrate-and-fire (LIF) neuron, referred to as the LIF with threshold fatigue, and show that it reproduce...
While the effects derived under the potential-outcomes framework required no particular model, we now need to decide how to model our data to obtain estimates. We first select models for the outcome and the mediator. Outcomes can be continuous, binary, or counts and can be modeled using a ...
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the length of the anomaly is the only parameter and no further threshold is required. Both LOF and Keogh’s algorithm find the predefined number of time instances exactly. While the discord finds them in one continuous time interval, LOF detects independent points along the whole data. The expe...
Time series generated by complex systems like financial markets and the earth’s atmosphere often represent superstatistical random walks: on short time scales, the data follow a simple low-level model, but the model parameters are not constant and can f