Sufficient dimension reduction for clustered data via finite mixture modelling
DOI10.1111/anzs.12349zbMath1521.62050OpenAlexW4207065224MaRDI QIDQ6051665
Linh H. Nghiem, Francis K. C. Hui
Publication date: 20 October 2023
Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/anzs.12349
repeated measuresrandom effectsmixture of expertsmixed modelsfinite mixture modelsindex modelscentral subspace
Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to environmental and related topics (62P12)
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Cites Work
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- Sparse Sliced Inverse Regression Via Lasso
- Semiparametric mixtures of regressions with single-index for model based clustering
- Estimation for the single-index models with random effects
- Local estimation for longitudinal semiparametric varying-coefficient partially linear model
- Dimension estimation in sufficient dimension reduction: a unifying approach
- Penalized quadratic inference functions for single-index models with longitudinal data
- Longitudinal data analysis using sufficient dimension reduction method
- On consistency and sparsity for sliced inverse regression in high dimensions
- Regression analysis under link violation
- Testing predictor contributions in sufficient dimension reduction.
- Dimensionality determination: a thresholding double ridge ratio approach
- Mini-batch learning of exponential family finite mixture models
- Model-based SIR for dimension reduction
- Mixtures of regressions with predictor-dependent mixing proportions
- Testing the number of components in a normal mixture
- An estimating equation approach to dimension reduction for longitudinal data
- A new local estimation method for single index models for longitudinal data
- Simultaneous fixed and random effects selection in finite mixture of linear mixed-effects models
- Hierarchical Selection of Fixed and Random Effects in Generalized Linear Mixed Models
- Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models
- Sufficient Dimension Reduction via Bayesian Mixture Modeling
- Sufficient dimension reduction for longitudinal data
- Order selection in finite mixture models: complete or observed likelihood information criteria?
- Sliced Inverse Regression for Dimension Reduction
- Generalized Partially Linear Single-Index Models
- Penalized Spline Estimation for Partially Linear Single-Index Models
- Applications: The Analysis of Crop Variety Evaluation Data in Australia
- A mixture model for dimension reduction
- On expectation propagation for generalised, linear and mixed models
- An Adaptive Estimation of Dimension Reduction Space
- A Semiparametric Approach to Dimension Reduction
- A Review on Dimension Reduction
- Series estimation for single‐index models under constraints
- Semiparametric Regression Using Variational Approximations
- Spatio-Temporal Analysis of Total Nitrate Concentrations Using Dynamic Statistical Models
- A validated information criterion to determine the structural dimension in dimension reduction models
- Model selection for mixture-based clustering for ordinal data
- Time Series: A Data Analysis Approach Using R
- A Multiple-Index Model and Dimension Reduction
- ESTIMATING COMPONENTS IN FINITE MIXTURES AND HIDDEN MARKOV MODELS
- Linear mixed models for longitudinal data
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