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Statistical challenges in high‐dimensional molecular and genetic epidemiology Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Shelley B. Bull, Irene L. Andrulis, Andrew D. Paterson
  • Published Date: Nov 15, 2017

Abstract Molecular and genetic association studies conducted in well‐characterized longitudinal cohorts offer a powerful approach to investigate factors...

Linear operator‐based statistical analysis: A useful paradigm for big data Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Bing Li
  • Published Date: Oct 27, 2017

Abstract In this article we lay out some basic structures, technical machineries, and key applications, of Linear Operator‐Based Statistical Analysis, and...

Online updating method with new variables for big data streams Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Chun Wang, Ming‐Hui Chen, Jing Wu, Jun Yan, Yuping Zhang, Elizabeth Schifano
  • Published Date: Aug 09, 2017

Abstract For big data arriving in streams online updating is an important statistical method that breaks the storage barrier and the computational barrier...

Likelihood inflating sampling algorithm Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Reihaneh Entezari, Radu V. Craiu, Jeffrey S. Rosenthal
  • Published Date: Oct 09, 2017

Abstract Markov Chain Monte Carlo (MCMC) sampling from a posterior distribution corresponding to a massive data set can be computationally prohibitive as...

Dynamic data science and official statistics Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Mary E. Thompson
  • Published Date: May 23, 2017

Abstract Many of the challenges and opportunities of data science have to do with dynamic factors: a growing volume of administrative and commercial data on...

Testing the heteroscedastic error structure in quantile varying coefficient models Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Irène Gijbels, Mohammed A. Ibrahim, Anneleen Verhasselt
  • Published Date: Nov 17, 2017

Abstract In mean regression the characteristic of interest is the conditional mean of the response given the covariates. In quantile regression the aim is...

Minimax robust active learning for approximately specified regression models Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Rui Nie, Douglas P. Wiens, Zhichun Zhai
  • Published Date: Aug 11, 2017

Abstract We address problems of model misspecification in active learning. We suppose that an investigator will sample training input points (predictors)...

Post‐selection inference for 1 ‐penalized likelihood models Early View

  • Journal: Canadian Journal of Statistics
  • Authors: Jonathan Taylor, Robert Tibshirani
  • Published Date: Mar 06, 2017

Abstract We present a new method for post‐selection inference for ℓ 1 ...

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