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Random forest missing data algorithms Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Fei Tang, Hemant Ishwaran
  • Published Date: Jun 13, 2017

Random forest (RF) missing data algorithms are an attractive approach for imputing missing data. They have the desirable properties of being able to handle mixed types of missing data,...

Bayesian kernel machine models for testing genetic pathway effects in prostate cancer prognosis Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Chang Xu, Sounak Chakraborty
  • Published Date: Jun 09, 2017

In this paper we propose a Bayesian semiparametric regression model to estimate and test the effect of a genetic pathway on prostate‐specific antigen (PSA) measurements for patients with...

A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Qiwei Li, Michele Guindani, Brian J. Reich, Howard D. Bondell, Marina Vannucci
  • Published Date: Jun 08, 2017

In this paper, we consider the problem of modeling a matrix of count data, where multiple features are observed as counts over a number of samples. Due to the nature of the data generating...

A wavelet threshold denoising procedure for multimodel predictions: An application to economic time series Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Livio Fenga
  • Published Date: Jul 31, 2017

Noise‐affected economic time series, realizations of stochastic processes exhibiting complex and possibly nonlinear dynamics, are dealt with. This is often the case of time series found in...

Comparative study of clustering techniques for real‐time dynamic model reduction Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Emilie Purvine, Eduardo Cotilla‐Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang
  • Published Date: Aug 24, 2017

Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or offline analysis is not adequate to...

Joining statistics and geophysics for assessment and uncertainty quantification of three‐dimensional seismic Earth models Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Carène Larmat, Monica Maceira, David M. Higdon, Dale N. Anderson
  • Published Date: Aug 29, 2017

Seismic inversions produce seismic models, which are 3‐dimensional (3D) images of wave velocity of the entire planet retrieved by fitting seismic measurements made on records of past...

A nonparametric test of independence between 2 variables Early View

  • Journal: Statistical Analysis and Data Mining: The ASA Data Science Journal
  • Authors: Bin Li, Qingzhao Yu
  • Published Date: Sep 13, 2017

A nonparametric statistic, called the roughness of concomitant ranks, is proposed for testing whether 2 quantitative vectors are dependent. The new testing procedure is highly...

A series of single array 2 m factorial search designs for even m Early View

  • Journal: Australian & New Zealand Journal of Statistics
  • Authors: Hooshang Talebi, Elham Jalali
  • Published Date: Nov 26, 2014

Summary By means of a search design one is able to search for and estimate a small set of non‐zero elements from the set of higher order factorial interactions in addition...

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