Results 111 to 120 of about 20,763 (296)

Collection of maximum likelihood gene trees with bootstrap replicates

, 2017
Maximum likelihood phylogeny generated via RAxML and associated nonparametric bootstrap replicates for each gene in our 95-locus ...
David C. Cannatella (429614), Zhang, Peng, Feng, Yan-Jie, Cannatella, David C., Dan Liang (158243), Hillis, David M., Yan-Jie Feng (3314904), Blackburn, David C., David C. Blackburn (244228), David B. Wake (264012), Peng Zhang (2071), David M. Hillis (429615), Wake, David B., Liang, Dan   +13 more
core   +1 more source

Machine Learning Hazard Estimation with Valid Bootstrap Inference for Generalized Progressive Hybrid Censoring

Mathematics
Reliability studies frequently employ progressive censoring schemes that remove surviving units during testing, yet statistical inference under such designs remains vulnerable to parametric model misspecification.
Sherif I. Ammar, Faizah T. Alamri, Faiza A. Althubyani, Mahmoud H. Abu-Moussa   +3 more
doaj   +1 more source

Unpacking early risks for peer victimization: A network analysis of early temperament and polygenic risk scores

JCPP Advances, EarlyView.
Abstract Background Children who show difficult temperament are at risk of peer victimisation, which in turn associates with numerous negative outcomes later in life. We used network analysis to examine whether specific aspects of difficult temperament contributed to these associations, and whether the links were moderated by variations in genetic ...
Tom C.‐H. Wu, Deniz Konac, Liliana Garcia‐Mondragon, Alex F. Martin, Barbara Maughan, Ted Barker   +5 more
wiley   +1 more source

Robust Estimation and Inference for Semiparametric and Nonparametric Regression Models

Mathematics
Parametric regression methods are efficient when correctly specified but are sensitive to model misspecification and outliers. Nonparametric regression offers greater flexibility at the cost of reduced interpretability and susceptibility to the curse of ...
Hamdy F. F. Mahmoud, Ahmed AbdelWahab A. Ali, Wael Mahmoud A. Mohamed   +2 more
doaj   +1 more source

Comparison of machine learning methods for prediction of venous thromboembolism among hospitalized adults

Journal of Hospital Medicine, EarlyView.
Abstract Background Hospital‐acquired venous thromboembolism (HA‐VTE) is a significant cause of morbidity and mortality among hospitalized adults. Accurate prediction of HA‐VTE is crucial for timely intervention and prevention. While logistic regression is widely used for the development of clinical prediction models, there is ongoing interest in the ...
Yeji Ko, Benjamin French, Jonathan S. Schildcrout, Merna El‐Rifai, Adam Wright, Benjamin F. Tillman, Amanda S. Mixon, Henry J. Domenico   +7 more
wiley   +1 more source

Statistical modeling of gold price data using generalized extreme value distribution: an inference based on parametric and nonparametric bootstrap confidence interval [PDF]

This study applies Extreme Value Theory (EVT) to model and quantify the risk associated with gold price fluctuations in the Malaysian market. Using daily gold price data from February 2010 to May 2023, the monthly maxima of negative daily log returns are
Ali, Norhaslinda, Mohd Kamarul Ariffin, Muhammad Firdaus   +1 more
core  

Figure 1 in Biogeographical analysis of Cameroonian puddle frogs and description of a new species of Phrynobatrachus (Anura: Phrynobatrachidae) endemic to Mount Oku, Cameroon

, 2009
Figure 1. Maximum likelihood phylogram inferred from mitochondrial nucleotide sequence data of 12S rRNA, valinetRNA, and 16S rRNA. Numbers above branches are nonparametric bootstrap proportions from PHYML analysis; numbers below branches are Bayesian ...
Zimkus, Breda M.
core   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Mammal species richness and functional dispersion.

, 2018
Comparison of species richness and functional dispersion along a forest regrowth gradient in the eastern Amazon. Boxplots show means and 95% confidence limits estimated via nonparametric bootstrap.
Paulo Estefano D. Bobrowiec (754291), Alexander Arévalo-Sandi (4971631), Darren Norris (623285), Victor Juan Ulises Rodriguez Chuma (4971628)   +3 more
core   +1 more source

Bootstrapping Nonparametric Prediction Intervals for Conditional Value-at-Risk with Heteroscedasticity

Journal of Probability and Statistics, 2019
Using bootstrap method, we have constructed nonparametric prediction intervals for Conditional Value-at-Risk for returns that admit a heteroscedastic location-scale model where the location and scale functions are smooth, and the function of the error ...
Emmanuel Torsen, Lema Logamou Seknewna
doaj   +1 more source