Pages that link to "Item:Q3585407"
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The following pages link to The horseshoe estimator for sparse signals (Q3585407):
Displaying 50 items.
- Simultaneous transformation and rounding (STAR) models for integer-valued data (Q66005) (← links)
- Sparsity information and regularization in the horseshoe and other shrinkage priors (Q86320) (← links)
- Achieving shrinkage in a time-varying parameter model framework (Q89526) (← links)
- Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity (Q114810) (← links)
- Bayesian Bootstrap Spike-and-Slab LASSO (Q127195) (← links)
- Inconsistency identification in network meta-analysis via stochastic search variable selection (Q158820) (← links)
- Compound Poisson processes, latent shrinkage priors and Bayesian nonconvex penalization (Q273588) (← links)
- Scaling it up: stochastic search structure learning in graphical models (Q273600) (← links)
- Conditions for posterior contraction in the sparse normal means problem (Q276234) (← links)
- Sub-optimality of some continuous shrinkage priors (Q335657) (← links)
- Geometric ergodicity of the Bayesian Lasso (Q367204) (← links)
- An alternative to the inverted gamma for the variances to modelling outliers and structural breaks in dynamic models (Q398210) (← links)
- Mean field variational Bayes for continuous sparse signal shrinkage: pitfalls and remedies (Q405332) (← links)
- Meta-analysis of functional neuroimaging data using Bayesian nonparametric binary regression (Q439162) (← links)
- Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector (Q470502) (← links)
- The horseshoe estimator: posterior concentration around nearly black vectors (Q485913) (← links)
- Mixtures of \(g\)-priors for Bayesian model averaging with economic applications (Q528107) (← links)
- Asymptotic Bayes-optimality under sparsity of some multiple testing procedures (Q638803) (← links)
- On Bayesian lasso variable selection and the specification of the shrinkage parameter (Q746286) (← links)
- Small area estimation with mixed models: a review (Q830271) (← links)
- Bayesian linear regression with sparse priors (Q888501) (← links)
- Bayesian quantile regression for single-index models (Q892421) (← links)
- Incorporating grouping information in Bayesian variable selection with applications in genomics (Q899018) (← links)
- Inferring constructs of effective teaching from classroom observations: an application of Bayesian exploratory factor analysis without restrictions (Q902925) (← links)
- Testing un-separated hypotheses by estimating a distance (Q1631558) (← links)
- Prior distributions for objective Bayesian analysis (Q1631565) (← links)
- Variable selection via penalized credible regions with Dirichlet-Laplace global-local shrinkage priors (Q1631579) (← links)
- Variable selection using shrinkage priors (Q1658484) (← links)
- High-dimensional multivariate posterior consistency under global-local shrinkage priors (Q1661340) (← links)
- Dual-semiparametric regression using weighted Dirichlet process mixture (Q1662051) (← links)
- Comment: A brief survey of the current state of play for Bayesian computation in data science at big-data scale (Q1705540) (← links)
- Model selection using mass-nonlocal prior (Q1726889) (← links)
- Default priors for the intercept parameter in logistic regressions (Q1727911) (← links)
- Tree ensembles with rule structured horseshoe regularization (Q1728658) (← links)
- Shrinkage, pretest, and penalty estimators in generalized linear models (Q1731260) (← links)
- Efficient Bayesian regularization for graphical model selection (Q1738143) (← links)
- Bayesian estimation of sparse signals with a continuous spike-and-slab prior (Q1747745) (← links)
- Regularization and confounding in linear regression for treatment effect estimation (Q1752011) (← links)
- Locally adaptive smoothing with Markov random fields and shrinkage priors (Q1752016) (← links)
- Penalising model component complexity: a principled, practical approach to constructing priors (Q1790379) (← links)
- Minimum message length inference of the Poisson and geometric models using heavy-tailed prior distributions (Q1799691) (← links)
- Hierarchical Bayes, maximum a posteriori estimators, and minimax concave penalized likelihood estimation (Q1951144) (← links)
- Penalized wavelets: embedding wavelets into semiparametric regression (Q1952243) (← links)
- Bayesian Lasso with neighborhood regression method for Gaussian graphical model (Q2013049) (← links)
- Joint mean-covariance estimation via the horseshoe (Q2022549) (← links)
- Understanding forecast reconciliation (Q2031082) (← links)
- Minimax predictive density for sparse count data (Q2040060) (← links)
- The horseshoe-like regularization for feature subset selection (Q2040669) (← links)
- Bayesian deconvolution and quantification of metabolites from \(J\)-resolved NMR spectroscopy (Q2057325) (← links)
- Dynamic regression models for time-ordered functional data (Q2057327) (← links)
