Pages that link to "Item:Q440250"
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The following pages link to A penalized maximum likelihood approach to sparse factor analysis (Q440250):
Displaying 26 items.
- Sparse estimation via nonconcave penalized likelihood in factor analysis model (Q261015) (← links)
- Interpreting latent variables in factor models via convex optimization (Q681494) (← links)
- Sparse factor regression via penalized maximum likelihood estimation (Q725684) (← links)
- A deep learning algorithm for high-dimensional exploratory item factor analysis (Q823855) (← links)
- Single- and multiple-group penalized factor analysis: a trust-region algorithm approach with integrated automatic multiple tuning parameter selection (Q823858) (← links)
- Estimation of an oblique structure via penalized likelihood factor analysis (Q1623658) (← links)
- Sparsest factor analysis for clustering variables: a matrix decomposition approach (Q1630876) (← links)
- Sparse principal component regression for generalized linear models (Q1662867) (← links)
- Sparse principal component regression with adaptive loading (Q1663268) (← links)
- Sparse exploratory factor analysis (Q1682447) (← links)
- A penalized likelihood method for structural equation modeling (Q1695631) (← links)
- Sparse principal component regression via singular value decomposition approach (Q2051586) (← links)
- Interpretability of composite indicators based on principal components (Q2095785) (← links)
- Regularized estimation for highly multivariate log Gaussian Cox processes (Q2302515) (← links)
- Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case (Q2318820) (← links)
- Linear models based on noisy data and the Frisch scheme (Q2808247) (← links)
- Variable selection via the weighted group Lasso for factor analysis models (Q2856545) (← links)
- Simultaneous variable and factor selection via sparse group lasso in factor analysis (Q5107489) (← links)
- Penalized partially linear models using sparse representations with an application to fMRI time series (Q5355829) (← links)
- Covariance structure estimation with Laplace approximation (Q6074739) (← links)
- Rotation to sparse loadings using \(L^p\) losses and related inference problems (Q6175690) (← links)
- Sparse and simple structure estimation via prenet penalization (Q6198871) (← links)
- Mediation analysis with latent factors using simultaneous group-wise and parameter-wise penalization (Q6548890) (← links)
- Sparse inference of structural equation modeling with latent variables for diffusion processes (Q6578486) (← links)
- Interpretable Sparse Proximate Factors for Large Dimensions (Q6620981) (← links)
- Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression (Q6665534) (← links)
