Efficient interaction selection for clustered data via stagewise ...

This work presents two stagewise estimation approaches to appropriately select models with interaction terms that can utilize generalized estimating equations ...

Efficient interaction selection for clustered data via stagewise generalized estimating equations. Stat Med. 2020 Sep 30;39(22):2855-2868. doi: 10.1002/sim.

Efficient interaction selection for clustered data via stagewise ...

This work presents two stagewise estimation approaches to appropriately select models with interaction terms that can utilize generalized ...

Efficient interaction selection for clustered data via stagewise ...

Request PDF | Efficient interaction selection for clustered data via stagewise generalized estimating equations | Model selection in the presence of ...

Stagewise generalized estimating equations with grouped variables ...

Efficient interaction selection for clustered data via stagewise generalized estimating equations · Gregory VaughanR. AseltineKun ChenJun Yan. Computer Science, ...

Gregory Vaughan, Associate Professor, Mathematical Sciences

Efficient interaction selection for clustered data via stagewise generalized estimating equations. Statistics in Medicine. Vaughan, G. (2020). Efficient big ...

sgee-package - Stagewise Generalized Estimating Equations - rdrr.io

... Stagewise regression with grouped covariates setting using ... Efficient interaction selection for clustered data via stagewise generalized estimating equations.

Stagewise Generalized Estimating Equations with Grouped ...

More Like this. Efficient interaction selection for clustered data via stagewise generalized estimating equations · https://doi.org/10.1002/sim.8574. Vaughan ...

sgee source: R/isee.R - rdrr.io

Efficient #' interaction selection for clustered data via stagewise generalized #' estimating equations. Department of Statistics, University of ...

农业科技信息资源共建共享平台

您所在的位置：首页文献传递详情页. 文献信息. Efficient interaction selection for clustered data via stagewise generalized estimating equations.

Interaction stagewise estimating equations - R

... interaction terms using one of two stagewise methods ... Efficient interaction selection for clustered data via stagewise generalized estimating equations.

Efficient big data model selection with applications to fraud detection

One field where this focus is pertinent is credit card fraud detection. Model selection approaches can identify key predictors for preventing fraud. Stagewise ...

Methods for sample size determination in cluster randomized trials

The most common and simplest design choice for a cluster randomized trial is the completely randomized, two-arm parallel-group design with fixed cluster sizes.

Cluster-robust inference: A guide to empirical practice - ScienceDirect

Although the choice of clustering structure is often controversial, or ... Practical and effective approaches to dealing with clustered data. Political ...

Clustered Embedding Learning for Recommender Systems - arXiv

domains: items have interaction data, while clusters have cluster ... by optimizing its efficiency in dealing with batch data. CEL-Lite ...

Efficient image restoration with style-guided context cluster and ...

To address this issue, we further propose a SCPI-UNet based on SCoC-UNet, which leverages a style-guided clustered point interaction (SCPI) ...

Jun Yan - Loop

Efficient interaction selection for clustered data via stagewise generalized estimating equations. Gregory Vaughan; Robert H. Aseltine; Kun Chen · Jun Yan.

Scalable efficient reproducible multi-task learning via data splitting

In contemporary application, multi-task learning's significance has surged. This paper presents a scalable, efficient variable selection method for ...

Revisiting clustering for efficient unsupervised dialogue structure ...

... interaction through an unsupervised learning. In ... Frey BJ, Dueck D (2007) Clustering by passing messages between data points.

Heterogeneity for the Win: One-Shot Federated Clustering

Compared with fitting a single global model to data across all device, jointly learning personal- ized (separate but related) models can boost the effective.