tulpa_latent: Latent factor specification for unmeasured confounders

In tulpa: Templated Unified Library for Posterior Approximation in Bayesian Hierarchical Models

Latent factor specification for unmeasured confounders

Description

Specify latent factors to capture shared unmeasured confounders between model processes. Latent factors are particularly useful when you suspect that both processes are driven by common unmeasured variables.

Value

The constructor documented in this family (latent_factor()) returns a tulpa_latent specification object consumed by ratio / multi-arm model packages built on tulpa (e.g. tulpaRatio), where the shared factor enters two or more linear predictors and cancels in the derived ratio. It is a multi-arm construct: the single-response tulpa() front door does not read it (for an in-formula latent Gaussian block on a single response, use latent(tgmrf(...))).

tulpa documentation built on Oct. 19, 2026, 5:09 p.m.