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
Toward precision in simulation of paediatric mitral valve repair using patient-specific fluid-structure interaction modelling. [PDF]
Eur Heart J Imaging Methods PractChristierson L +8 more
europepmc +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
A 'worthy disciple of Galen', 'ardent sportsman' and 'expert swordsman': Henry Kipping (1726-1785) apothecary and surgeon at Brighton, England. [PDF]
J Med BiogrCooper MJ, Heath J.
europepmc +1 more source
The life and work of Ernest Sydney Keeping
Canadian Journal of Statistics, EarlyView.Abstract This article reviews the life and contributions of Ernest S. Keeping (1895–1984), a British‐born physicist who became a mathematics professor at the University of Alberta in 1929. He played a pivotal role in shaping the university's Mathematics Department, serving as its head from 1954 to 1961, and continuing to teach until 1970, nine years ...
David R. Bellhouse, Christian Genest
wiley +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
Model selection for causal inference in missing exposure problems
Canadian Journal of Statistics, EarlyView.Abstract In causal inference, properly selecting the propensity score (PS) model is an important topic and has been widely investigated in observational studies. However, there are very few studies investigating the model selection issue for causal inference when the exposure is missing at random (MAR). When the exposure variable contains missing data,
Yuliang Shi, Yeying Zhu, Joel A. Dubin
wiley +1 more source
Geometrically nonlinear high-fidelity aerostructural optimization for highly flexible wings. [PDF]
Struct Multidiscipl OptimGray AC, Kennedy GJ, Martins JRRA.
europepmc +1 more source
extBatchMarking: An R package for hidden Markov models for extended batch data
Canadian Journal of Statistics, EarlyView.Abstract We describe a new R package for extended batch‐mark methods. Extended batch marking is a valuable and efficient technique for estimating population sizes and survival probabilities of wild animals. It assigns the same identifier to a group of animals simultaneously, allowing researchers to track their survival over time.
Kehinde Olobatuyi +4 more
wiley +1 more source