Results 211 to 220 of about 5,352,065 (277)

Challenges and alternatives to empirical orthogonal functions for earth system data. [PDF]

Sci Rep
Shields CA, DeSantis D, Jonko A, Lee J, Caron JM, Phillips AS, Fasullo J.   +6 more
europepmc   +1 more source

Regularized reduced rank regression for mixed predictor and response variables

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract In this paper, we introduce the Generalized Mixed Regularized Reduced Rank Regression model (GMR4), an extension of the GMR3 model designed to improve performance in high‐dimensional settings. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables, while also allowing for mixed‐type predictors through optimal ...
Lorenza Cotugno, Mark de Rooij, Roberta Siciliano   +2 more
wiley   +1 more source

Parallel fusion model for complex multi-source vibration time-series prediction. [PDF]

Sci Rep
Huang W, Xu J.
europepmc   +1 more source

Multidimensional unipolar IRT and applications to the measurement of print exposure

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Item response theory (IRT) has been a prominent modelling framework in educational and psychological measurement. Traditional IRT models are bipolar, commonly assuming symmetric measurement link functions and symmetric trait distributions over a latent continuum unbounded at both ends. However, many measured constructs, such as print exposure,
Qi (Helen) Huang, Daniel M. Bolt
wiley   +1 more source

Competing risk model with a nonparametric form of relative risks. [PDF]

Lifetime Data Anal
Cho Y, Du P.
europepmc   +1 more source

Sensitivity analysis for unmeasured pretreatment confounders in causal mediation analysis with debiased machine learning

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Sensitivity analysis for unmeasured confounders is essential for assessing the robustness of causal mediation conclusions. Most existing methods rely on parametric assumptions, which are ill‐suited for machine learning‐based estimators that are not tied to specific parametric models.
Xiao Liu, Cameron McCann
wiley   +1 more source

A hybrid transformer-BiLSTM model optimized with Firefly Algorithm for network traffic anomaly detection. [PDF]

PLoS One
Luo D, Wang W, Liu X, Yang W, Hu K, Zhang J.   +5 more
europepmc   +1 more source

Survey on Visualization of Information Diffusion over Networks

Computer Graphics Forum, EarlyView.
Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl, M. Sondag, V. Filipov, M. Tuscher, S. Rajendran, S. Miksch, D. Archambault, A. Arleo, T. von Landesberger   +8 more
wiley   +1 more source

Thalamic modulation of cortical linearity across arousal states. [PDF]

Sci Adv
Müller EJ, Munn BR, Baracchini G, Fulcher BD, Medel V, Redinbaugh MJ, Saalmann YB, Wehrman JJ, Sanders RD, Brunton BW, Brunton SL, Shine JM.   +11 more
europepmc   +1 more source

The Story(line) So Far: A Survey on Storyline Visualization

Computer Graphics Forum, EarlyView.
Abstract Storyline visualizations model narratives as temporal networks, using x‐monotone lines to represent entities and their interactions over time. This technique offers an intuitive way to reveal structural patterns over time, such as character co‐occurrence and narrative flow.
S. Di Bartolomeo, A. Dobler, V. Filipov, M. Nöllenburg, H. Ehlers   +4 more
wiley   +1 more source