Results 181 to 190 of about 14,957 (259)

Inference for Deep Neural Network Estimators in Generalized Nonparametric Models. [PDF]

J Am Stat Assoc
Meng X, Li Y.
europepmc   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

A Repeated Block Perturbation Subsampling for Large-Scale Longitudinal Data. [PDF]

J Stat Theory Pract
Yao Y, Lee JH, Jin Z.
europepmc   +1 more source

A partial envelope approach for modelling multivariate spatial‐temporal data

Canadian 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, Wenbo Wu, Victor De Oliveira, Keying Ye   +3 more
wiley   +1 more source

Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation. [PDF]

Philos Trans A Math Phys Eng Sci
Chung J, Miller SM, Sabate Landman M, Saibaba AK.   +3 more
europepmc   +1 more source

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

Canadian 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

Detrended Cross-Correlations and Their Random Matrix Limit: An Example from the Cryptocurrency Market. [PDF]

Entropy (Basel)
Drożdż S, Jarosz P, Kwapień J, Skupień M, Wątorek M.   +4 more
europepmc   +1 more source

Vine copula knockoffs for variable selection in gene expression studies

Canadian Journal of Statistics, EarlyView.
Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina, Alejandro Román Vásquez, Graciela González Farías, Gabriel Escarela   +3 more
wiley   +1 more source

Interpretable and extrapolation-stable model for predicting nanofluid thermal conductivity. [PDF]

Sci Rep
Zinhom E, Radwan SS, Elmasry A, Sharaf MAM, Nassar MM.   +4 more
europepmc   +1 more source

Large parameter asymptotic analysis for homogeneous normalized random measures with independent increments

Canadian Journal of Statistics, EarlyView.
Abstract Homogeneous normalized random measures with independent increments represent a broad class of Bayesian nonparametric priors and thus are widely used. In this article, we obtain the strong law of large numbers, the central limit theorem (CLT), and the functional central limit theorem (fCLT) of such measures when the concentration parameter a ...
Junxi Zhang, Shui Feng, Yaozhong Hu
wiley   +1 more source