Return samples from a mash object
get_samples(m)The mash fit.
simdata = simple_sims(50,5,1)
data = mash_set_data(simdata$Bhat, simdata$Shat)
m = mash(data, cov_canonical(data), posterior_samples=5, algorithm='R')
#> - Computing 200 x 141 likelihood matrix.
#> - Likelihood calculations took 0.03 seconds.
#> - Fitting model with 141 mixture components.
#> - Model fitting took 0.17 seconds.
#> - Computing posterior matrices.
#> - Computation allocated took 0.12 seconds.
get_samples(m)
#> , , sample_1
#>
#> condition_1 condition_2 condition_3 condition_4 condition_5
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#> effect_2 -0.717799776 -0.7177997737 -0.7177997737 -0.7177997737 -0.7177997737
#> effect_3 -3.174587189 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_4 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_5 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_6 1.600441026 1.6004410093 1.6004410093 1.6004410093 1.6004410093
#> effect_7 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_8 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_9 -0.453127999 -0.4531280047 -0.4531280047 -0.4531280047 -0.4531280047
#> effect_10 0.453952684 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_11 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_12 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_13 0.820717884 0.8207178889 0.8207178889 0.8207178889 0.8207178889
#> effect_14 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> effect_15 0.000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
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#>
#> , , sample_2
#>
#> condition_1 condition_2 condition_3 condition_4 condition_5
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