Jan 10, 2012 · When multiple data owners possess records on different subjects with the same set of attributes—known as horizontally partitioned data—the data owners can improve analyses by concatenating their databases. However, concatenation of data may be infeasible because of confidentiality concerns.
We present secure computation protocols for Bayesian model averaging and model selection for both linear regression and probit regression. Using simulations based on genuine data, we illustrate the approach for probit regression, and show that it can provide reasonable model selection outputs.
When multiple data owners possess records on different subjects with the same set of attributes-known as horizontally partitioned data-the data owners can ...
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Secure Bayesian model averaging for horizontally partitioned data. J Ghosh, JP Reiter. Statistics and Computing 23 (3), 311-322, 2013. 10, 2013. BAS: Bayesian model averaging using Bayesian adaptive sampling. M Clyde, M Littman, J Ghosh. R package version 1, 2012. 6, 2012. Sandwich algorithms for Bayesian variable ...
Reiter (2013), "Secure Bayesian Model Averaging for Horizontally Partitioned Data", Statistics and Computing, 23(3), 311-322 pdf. The final version of the ... Technical Reports. Joyee Ghosh*, Aixin Tan*, and Lan Luo (2024+), "Online Bayesian variable selection and Bayesian model averaging for streaming data", pdf.
In this paper, we present a protocol for secure adaptive regression splines that allows for flexible, semi-automatic regression modeling. This reduces the risk of model mis-specification inherent in secure computation settings. We illustrate the protocol with air pollution data.
Estimating second order characteristics of point processes with known independent noise · Secure Bayesian model averaging for horizontally partitioned data · Parallel tempering with equi-energy moves · Straightforward intermediate rank tensor product smoothing in mixed models.
Secure Bayesian model averaging for horizontally partitioned data. Stat ... Secure computation with horizontally partitioned data using adaptive regression ...
6 days ago · In this article, our goal is to develop a method for Bayesian model averaging in linear regression models to accommodate heavier tailed error distributions than the normal distribution. Motivated by the use of the Huber loss function in presence of outliers, Park and Casella, (2008) proposed the ...
Jan 15, 2023 · Accurate pre-harvest prediction of wheat yield through secondary traits helps to facilitate plant breeding and reduce costs. Machine learning (ML) algorithms are increasingly applied to grain yield with remote sensing data. However, the performance of individual ML algorithms varies for different ...
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