Pages that link to "Item:Q375219"
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The following pages link to Two simple examples for understanding posterior \(p\)-values whose distributions are far from unform (Q375219):
Displaying 16 items.
- Why preferring parametric forecasting to nonparametric methods? (Q530528) (← links)
- Modeling within-item dependencies in parallel data on test responses and brain activation (Q823875) (← links)
- Bayesian threshold selection for extremal models using measures of surprise (Q1623822) (← links)
- Posterior predictive \(p\)-values with Fisher randomization tests in noncompliance settings: test statistics vs discrepancy measures (Q1631569) (← links)
- Approximation of Bayesian predictive \(p\)-values with regression ABC (Q1752002) (← links)
- Preelectoral polls variability: a hierarchical Bayesian model to assess the role of house effects with application to Italian elections (Q2135367) (← links)
- Latent likelihood ratio tests for assessing spatial kernels in epidemic models (Q2204864) (← links)
- A simple method for comparing complex models: Bayesian model comparison for hierarchical multinomial processing tree models using Warp-III bridge sampling (Q2331157) (← links)
- Posterior predictive checking of multiple imputation models (Q3451381) (← links)
- Posterior predictive checks can and should be Bayesian: Comment on Gelman and Shalizi, ‘Philosophy and the practice of Bayesian statistics’ (Q4614593) (← links)
- Modeling for Dynamic Ordinal Regression Relationships: An Application to Estimating Maturity of Rockfish in California (Q4690928) (← links)
- Calibration of posterior predictive <i>p</i>-values for model checking (Q5065240) (← links)
- Modeling the Marked Presence-Only Data: A Case Study of Estimating the Female Sex Worker Size in Malawi (Q5881060) (← links)
- Joint Bayesian analysis of multiple response-types using the hierarchical generalized transformation model (Q6121614) (← links)
- Global–local shrinkage multivariate logit-beta priors for multiple response-type data (Q6494412) (← links)
- A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification (Q6628030) (← links)
