Clustered Coefficient Regression Models for Poisson Process with an Application to Seasonal Warranty Claim Data
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Publication:6631159
DOI10.1080/00401706.2023.2190779MaRDI QIDQ6631159
Zhengyuan Zhu, Xin Wang, Xin Zhang
Publication date: 31 October 2024
Published in: Technometrics (Search for Journal in Brave)
Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nearly unbiased variable selection under minimax concave penalty
- Cox's regression model for counting processes: A large sample study
- High-dimensional integrative analysis with homogeneity and sparsity recovery
- Seasonal warranty prediction based on recurrent event data
- Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data
- Subgroup analysis for heterogeneous additive partially linear models and its application to car sales data
- A Semiparametric Model for the Analysis of Recurrent-Event Panel Data
- Regression Methods for Poisson Process Data
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Spatial Homogeneity Pursuit of Regression Coefficients for Large Datasets
- Tuning parameter selectors for the smoothly clipped absolute deviation method
- Identifying subgroups of age and cohort effects in obesity prevalence
- Learning Coefficient Heterogeneity over Networks: A Distributed Spanning-Tree-Based Fused-Lasso Regression
- Spatial heterogeneity automatic detection and estimation
- Subgroup analysis in the heterogeneous Cox model
- Exploration of heterogeneous treatment effects via concave fusion
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