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)

Arguments

MegaLMM_state

The model after calling initialize_variables_MegaLMM

Value

The estimated memory size in bytes

Details

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()

Examples

estimate_memory_initialization_MegaLMM(MegaLMM_state)
#> Loading required package: pryr
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'MegaLMM_state' not found