Pages that link to "Item:Q4935366"
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The following pages link to Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation (Q4935366):
Displaying 12 items.
- Determination of correlations in multivariate longitudinal data with modified Cholesky and hypersphere decomposition using Bayesian variable selection approach (Q6627941) (← links)
- Graphical models for mean and covariance of multivariate longitudinal data (Q6627998) (← links)
- Bayesian semi-parametric modeling of covariance matrices for multivariate longitudinal data (Q6628401) (← links)
- A novel robust estimation for high-dimensional precision matrices (Q6629954) (← links)
- A Covariate-Regulated Sparse Subspace Learning Model and Its Application to Process Monitoring and Fault Isolation (Q6631131) (← links)
- A semiparametric Bayesian approach for analyzing longitudinal data from multiple related groups (Q6633140) (← links)
- Adaptive Shrinkage in Bayesian Vector Autoregressive Models (Q6634836) (← links)
- Hidden Markov models for multivariate panel data (Q6643214) (← links)
- Modelling correlation matrices in multivariate data, with application to reciprocity and complementarity of child-parent exchanges of support (Q6665488) (← links)
- Multivariate robust linear models for multivariate longitudinal data (Q6667477) (← links)
- Ultra-high dimensional longitudinal quantile feature screening based on modified Cholesky decomposition (Q6670794) (← links)
- Bandwidth selection for large covariance and precision matrices (Q6671919) (← links)
