scholarly journals Variable Selection in Bayesian Smoothing Spline ANOVA Models: Application to Deterministic Computer Codes

Technometrics ◽  
2009 ◽  
Vol 51 (2) ◽  
pp. 110-120 ◽  
Author(s):  
Brian J. Reich ◽  
Curtis B. Storlie ◽  
Howard D. Bondell
Keyword(s):  
Variable Selection ◽  
Smoothing Spline ◽  
Computer Codes ◽  
Smoothing Spline Anova ◽  
Bayesian Smoothing

Sensitivity analysis in classification using Bayesian smoothing spline ANOVA probit regression

2021 ◽  
Author(s):  
Chunzhe Zhang ◽  
Curtis B. Storlie ◽  
Thomas C. M. Lee
Keyword(s):  
Sensitivity Analysis ◽  
Smoothing Spline ◽  
Probit Regression ◽  
Smoothing Spline Anova ◽  
Bayesian Smoothing

scholarly journals Calibration of Computational Models With Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA

2015 ◽  
Vol 110 (509) ◽  
pp. 68-82 ◽  
Author(s):  
Curtis B. Storlie ◽  
William A. Lane ◽  
Emily M. Ryan ◽  
James R. Gattiker ◽  
David M. Higdon
Keyword(s):  
Computational Models ◽  
Smoothing Spline ◽  
Smoothing Spline Anova ◽  
Bayesian Smoothing

scholarly journals Speakers’ rapidly-updated expectations influence prosodic realization of information structure

2017 ◽  
Vol 2 ◽  
pp. 51
Author(s):  
Iris Chuoying Ouyang ◽  
Sasha Spala ◽  
Elsi Kaiser
Keyword(s):  
Perspective Taking ◽  
Information Structure ◽  
Smoothing Spline ◽  
Computer Screen ◽  
Interactive Game ◽  
Knowledge State ◽  
Verbal Instructions ◽  
Production Experiment ◽  
Smoothing Spline Anova

A production experiment was conducted to investigate the role of perspective-taking in the prosodic marking of information structure. Participants played an interactive game in which they produced verbal instructions that directed an addressee to place objects in locations on the computer screen. We manipulated (i) the participants’ assumptions about the addressee’s familiarity with the objects and (ii) the addressee’s accuracy in identifying the objects. F0 measurements of the participants’ utterances were analyzed with Smoothing-spline ANOVA models. We find that speakers’ expectations about the addressee’s knowledge state influence the prosodic realization of both new and given information, and that speakers rapidly update their expectations based on the addressee’s behavior during the conversation.

Model diagnostics for smoothing spline ANOVA models

2004 ◽  
Vol 32 (4) ◽  
pp. 347-358 ◽  
Author(s):  
Chong Gu
Keyword(s):  
Smoothing Spline ◽  
Model Diagnostics ◽  
Smoothing Spline Anova

scholarly journals Smoothing spline ANOVA for exponential families, with application to the Wisconsin Epidemiological Study of Diabetic Retinopathy : the 1994 Neyman Memorial Lecture

1995 ◽  
Vol 23 (6) ◽  
pp. 1865-1895 ◽  
Author(s):  
Grace Wahba ◽  
Yuedong Wang ◽  
Chong Gu ◽  
Ronald Klein ◽  
Barbara Klein
Keyword(s):  
Diabetic Retinopathy ◽  
Epidemiological Study ◽  
Exponential Families ◽  
Smoothing Spline ◽  
Memorial Lecture ◽  
Smoothing Spline Anova

Smoothing Spline ANOVA with Component-Wise Bayesian "Confidence Intervals"

1993 ◽  
Vol 2 (1) ◽  
pp. 97 ◽  
Author(s):  
Chong Gu ◽  
Grace Wahba
Keyword(s):  
Confidence Intervals ◽  
Smoothing Spline ◽  
Smoothing Spline Anova

Using recursive algorithms for the efficient identification of smoothing spline ANOVA models

2010 ◽  
Vol 94 (4) ◽  
pp. 367-388 ◽  
Author(s):  
Marco Ratto ◽  
Andrea Pagano
Keyword(s):  
Smoothing Spline ◽  
Recursive Algorithms ◽  
Smoothing Spline Anova

scholarly journals Bayes Factors for Smoothing Spline ANOVA

2016 ◽  
Vol 11 (4) ◽  
pp. 957-975
Author(s):  
Chin-I. Cheng ◽  
Paul L. Speckman
Keyword(s):  
Bayes Factors ◽  
Smoothing Spline ◽  
Smoothing Spline Anova

scholarly journals Variable selection for non-parametric quantile regression via smoothing spline analysis of variance

Stat ◽  
2013 ◽  
Vol 2 (1) ◽  
pp. 255-268 ◽  
Author(s):  
Chen-Yen Lin ◽  
Howard Bondell ◽  
Hao Helen Zhang ◽  
Hui Zou
Keyword(s):  
Variable Selection ◽  
Quantile Regression ◽  
Analysis Of Variance ◽  
Smoothing Spline ◽  
Selection For ◽  
Non Parametric
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