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Builds a start_vals list for ame or lame from an ALS point estimate. This is useful when the ALS fit has already found a good latent-space solution and the MCMC chain should start near that solution rather than from diffuse random values.

Usage

als_start_vals(fit, jitter = 0, seed = NULL)

Arguments

fit

a fitted ame_als, lame_als, or dynamic ALS object returned by lame with method = "als".

jitter

non-negative standard deviation for independent Gaussian perturbations added to numeric starting values. Use a small positive value for multiple MCMC chains.

seed

optional integer seed used for the jitter.

Value

A list that can be passed to start_vals. For a dynamic ALS fit it also carries rho_uv, sigma_uv, rho_ab, and sigma_ab, so the MCMC run starts its AR(1) hyperparameters from the ALS solution. Read these as starting values rather than estimates: the persistences are the values the ALS smoothness penalty used (the prior means unless prior set them), and the innovation scales are implied by the fitted paths, which the penalty shrinks, so they run below the posterior scale.