Pages that link to "Item:Q313077"

The following pages link to How hierarchical models improve point estimates of model parameters at the individual level (Q313077):

Displaying 10 items.

• Empirical priors for reinforcement learning models (Q285948) (← links)
• Hierarchical Bayesian models of reinforcement learning: introduction and comparison to alternative methods (Q825147) (← links)
• Hierarchical multinomial modeling to explain individual differences in children's clustering in free recall (Q826862) (← links)
• RT-MPTs: process models for response-time distributions based on multinomial processing trees with applications to recognition memory (Q1645047) (← links)
• The statistical structures of reinforcement learning with asymmetric value updates (Q1736016) (← links)
• Decomposition-based gradient estimation algorithms for multivariate equation-error autoregressive systems using the multi-innovation theory (Q2003302) (← links)
• Biases in estimating the balance between model-free and model-based learning systems due to model misspecification (Q2332840) (← links)
• (Q3486665) (← links)
• RT-MPTs: process models for response-time distributions with diffusion-model kernels (Q6595392) (← links)
• Bayesian parameter inference for epithelial mechanics (Q6671176) (← links)