View source: R/helper_functions.R
estimate_memory_initialization_MegaLMM | R Documentation |
the initialize_MegaLMM()
function can take a while to run, especially
when there are multiple random effects, large numbers of observations, and multiple
groups of traits (with different missing data patterns, stored in the Missing_data_map
).
Approximately, the initialization time and memory requirements will be linear in the
number of groups of traits, and scale with h2_divisions^(# random effects).
estimate_memory_initialization_MegaLMM(MegaLMM_state)
MegaLMM_state |
The model after calling |
This function will initialize the MegaLMM model for a single h2 vector and extrapolate
to the full grid of h2 vectors, enabeling you to estimate if you have enough
memory allocated to call initialize_MegaLMM()
The estimated memory size in bytes
estimate_memory_posterior
estimate_memory_initialization_MegaLMM(MegaLMM_state)
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