Optimal subsampling for regression with mixed‐type predictors
Canadian Journal of Statistics, EarlyView.Abstract Subsampling has emerged as an appealing strategy to mitigate the computational and storage challenges imposed by large datasets. Recent subsampling techniques have shown notable computational gains for data dominated by numerical predictors. However, real‐world datasets frequently contain both numerical and categorical predictors.
Jiaqing Zhu, Lin Wang, Fasheng Sun
wiley +1 more source
Group-Specific Nonlinear Mixed Effects Models for Longitudinal Data With Realignment of Time. [PDF]
Stat MedLiu Z, Gao S.
europepmc +1 more source
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
Molecular surveillance of multiplicity of infection, haplotype frequencies, and prevalence in infectious diseases. [PDF]
PLoS Comput BiolTsoungui Obama HCJ, Schneider KA.
europepmc +1 more source
Extreme conditional quantile estimation for time series
Canadian Journal of Statistics, EarlyView.Abstract We consider the estimation of an extreme conditional quantile QY(1−p|x0)$$ {Q}_Y\left(1-p|{x}_0\right) $$ for a heavy‐tailed distribution in the case of a strictly stationary time series (Xt,Yt)t∈ℤ$$ {\left({X}_t,{Y}_t\right)}_{t\in \mathbb{Z}} $$. Here, QY(·|x0)$$ {Q}_Y\left(\cdotp |{x}_0\right) $$ denotes the conditional quantile function of
Yuri Goegebeur +2 more
wiley +1 more source
Sparse maximum likelihood estimation of regression models
Canadian Journal of Statistics, EarlyView.Abstract For regression model selection and estimation, we study a small set of candidate models of maximum likelihood from which all information criteria such as the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) choose their models.
Min Tsao
wiley +1 more source
Integrating Meta-Analysis Into a Specific Study (InMASS) for Estimating the Target-Population Average Treatment Effect. [PDF]
Biom JHanada K, Kojima M.
europepmc +1 more source
Learning sparse mixture‐of‐experts generalized linear models in ultrahigh dimensions
Canadian Journal of Statistics, EarlyView.Abstract Motivated by the challenges of heterogeneity and high dimensionality in the analysis of modern data, we investigate continuous regularization methods for learning sparse mixture‐of‐experts generalized linear models (MoE‐GLM). Although there are foundational results about regularized estimators in a broad class of regression models including ...
Pengqi Liu, Abbas Khalili
wiley +1 more source
Approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model using Monte Carlo sampling. [PDF]
Theor Appl GenetHeikkilä A +4 more
europepmc +1 more source
Frequency-dependent modulation of foveal contrast sensitivity by fine-scale exogenously triggered attention. [PDF]
ElifeGuzhang Y, Jaeger TF, Poletti M.
europepmc +1 more source