Pages that link to "Item:Q2426740"

The following pages link to On posterior consistency in nonparametric regression problems (Q2426740):

Displaying 50 items.

• Stochastic expansions using continuous dictionaries: Lévy adaptive regression kernels (Q98918) (← links)
• On asymptotic properties of Bayesian partially linear models (Q395922) (← links)
• Posterior consistency of nonparametric conditional moment restricted models (Q449980) (← links)
• Bayesian nonparametric estimation and consistency of mixed multinomial logit choice models (Q637076) (← links)
• Posterior convergence for Bayesian functional linear regression (Q739583) (← links)
• A general robust t-process regression model (Q829720) (← links)
• Adaptive Bayesian estimation using a Gaussian random field with inverse gamma bandwidth (Q834358) (← links)
• Posterior consistency of Gaussian process prior for nonparametric binary regression (Q869978) (← links)
• On Bayesian asymptotics in stochastic differential equations with random effects (Q893977) (← links)
• Asymptotic properties of posterior distributions in nonparametric regression with non-Gaussian errors (Q904050) (← links)
• Rates of contraction of posterior distributions based on Gaussian process priors (Q930663) (← links)
• Posterior consistency for semi-parametric regression problems (Q1395941) (← links)
• A review of Bayesian asymptotics in general insurance applications (Q1707556) (← links)
• Bayesian consistency for regression models under a supremum distance (Q1926383) (← links)
• Consistency of the posterior distribution and MLE for piecewise linear regression (Q1950863) (← links)
• Posterior convergence and model estimation in Bayesian change-point problems (Q1952049) (← links)
• The consistency of posterior distributions in nonparametric problems (Q1970478) (← links)
• A fast and calibrated computer model emulator: an empirical Bayes approach (Q2058785) (← links)
• Consistent online Gaussian process regression without the sample complexity bottleneck (Q2058904) (← links)
• Posterior consistency of random effects models for binary data (Q2276171) (← links)
• Learning semiparametric regression with missing covariates using Gaussian process models (Q2297240) (← links)
• On classical and Bayesian asymptotics in stochastic differential equations with random effects having mixture normal distributions (Q2306245) (← links)
• Posterior concentration for a misspecified Bayesian regression model with functional covariates (Q2306246) (← links)
• Low information omnibus (LIO) priors for Dirichlet process mixture models (Q2316979) (← links)
• A nonparametric Bayesian methodology for regression discontinuity designs (Q2317304) (← links)
• Rates of contraction with respect to \(L_2\)-distance for Bayesian nonparametric regression (Q2326065) (← links)
• Minimax-optimal nonparametric regression in high dimensions (Q2343958) (← links)
• Bayesian consistency for Markov models (Q2352339) (← links)
• Bayesian semiparametric Wiener system identification (Q2356659) (← links)
• Asymptotic properties of nonparametric estimation and quantile regression in Bayesian structural equation models (Q2418505) (← links)
• Bayesian nonparametric regression with varying residual density (Q2434133) (← links)
• Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors (Q2643290) (← links)
• Sup–Hellinger consistency for local density regression (Q2807770) (← links)
• Bayesian spectral analysis models for quantile regression with Dirichlet process mixtures (Q2811275) (← links)
• Consistency of Posterior Distributions for Heteroscedastic Nonparametric Regression Models (Q2859312) (← links)
• Penalized Gaussian process regression and classification for high-dimensional nonlinear data (Q2893384) (← links)
• A Gaussian process regression approach to a single-index model (Q3021173) (← links)
• A Direct Approach to Understanding Posterior Consistency of Bayesian Regression Problems (Q3100653) (← links)
• Gaussian Process Models for Non Parametric Functional Regression with Functional Responses (Q3458081) (← links)
• Adaptive Bayesian Procedures Using Random Series Priors (Q3460673) (← links)
• Posterior contraction in Gaussian process regression using Wasserstein approximations (Q4603714) (← links)
• (Q5053265) (← links)
• Bayesian quantile regression and variable selection for partial linear single-index model: Using free knot spline (Q5085943) (← links)
• Convergence of Gaussian Process Regression with Estimated Hyper-Parameters and Applications in Bayesian Inverse Problems (Q5139353) (← links)
• Sequential Design for Ranking Response Surfaces (Q5269860) (← links)
• Locally Adaptive Bayes Nonparametric Regression via Nested Gaussian Processes (Q5406371) (← links)
• Posterior consistency for the spectral density of non‐Gaussian stationary time series (Q6049786) (← links)
• Bayesian sparse seemingly unrelated regressions model with variable selection and covariance estimation via the horseshoe+ (Q6080791) (← links)
• Empirical Bayesian analysis through the lens of a particular class of constrained Bayesian hierarchical models (Q6541816) (← links)
• Flexible regularized estimation in high-dimensional mixed membership models (Q6561268) (← links)