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A Varying-Coefficient Additive Hazard Model for Recurrent Events Data.
Stat Med
February 2025
Department of Statistics and Data Science, National University of Singapore, Singapore, Singapore.
The additive hazard model, which focuses on risk differences rather than risk ratios, has been widely applied in practice. In this paper, we consider an additive hazard model with varying coefficients to analyze recurrent events data. The model allows for both varying and constant coefficients.
View Article and Find Full Text PDFOn the Convergence Rate for the Longest at Most -Contaminated Runs of Heads.
Entropy (Basel)
January 2025
Faculty of Informatics, University of Debrecen, Kassai Street 26, 4028 Debrecen, Hungary.
In this paper, we study the usual coin tossing experiment. We call a run at most -contaminated, if it contains at most tails. We approximate the distribution of the length of the longest at most -contaminated runs.
View Article and Find Full Text PDFNodewise Parameter Aggregation for Psychometric Networks.
Multivariate Behav Res
January 2025
Department of Psychology, University of California, Davis, Davis, CA, USA.
Psychometric networks can be estimated using nodewise regression to estimate edge weights when the joint distribution is analytically difficult to derive or the estimation is too computationally intensive. The nodewise approach runs generalized linear models with each node as the outcome. Two regression coefficients are obtained for each link, which need to be aggregated to obtain the edge weight (i.
View Article and Find Full Text PDFQuantum transport under oscillatory drive with disordered amplitude.
J Phys Condens Matter
January 2025
Physics, Indian Institute of Science Education and Research Bhopal, Bypass Road Bhauri, Bhopal, 462066, INDIA.
We investigate the dynamics of non-interacting particles in a one-dimensional tight-binding chain in the presence of an electric field with random amplitude drawn from a Gaussian distribution, and explicitly focus on the nature of quantum transport. We derive an exact expression for the probability propagator and the mean-squared displacement in the clean limit and generalize it for the disordered case using the Liouville operator method. Our analysis reveals that in the presence a random static field, the system follows diffusive transport; however, an increase in the field strength causes a suppression in the transport and thus asymptotically leads towards localization.
View Article and Find Full Text PDFExplore poverty with statistical modeling: The bivariate polynomial binary logit regression (BPBLR).
MethodsX
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Sepuluh Nopember Institute of Technology, Airlangga University, Mulawarman University, Indonesia.
Logit regression (or logistic regression) is a statistical analysis of categorical data. The binary responses have two categories. We present the Bivariate Polynomial Binary Logit Regression (BPBLR), which extends logit regression by modeling two correlated binary response variables.
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