I have implemented a Bayesian model and I am interested in extracting the results. I’d like to first assess convergence of the MCMC chains but also extract the values for the parameters.
chain = sample(model_fun, sampler, MCMCThreads(), 10000, 4; progress=false);
group(chain, :y)
This prints out the following summary:
Chains MCMC chain (10000×41×4 Array{Float64, 3}):
Iterations = 1:1:10000
Number of chains = 4
Samples per chain = 10000
Wall duration = 507.61 seconds
Compute duration = 2027.93 seconds
parameters = y[12], y[13], y[14], y[15], y[16], y[17], y[18], y[19], y[20], y[21], y[22], y[23], y[24], y[25], y[26], y[27], y[28], y[29], y[30], y[31], y[32], y[33], y[34], y[35], y[36], y[37], y[38], y[39], y[40], y[41], y[42], y[43], y[44], y[45], y[46], y[47], y[48], y[49], y[50], y[51], y[52]
internals =
Summary Statistics
parameters mean std naive_se mcse ess rhat ess_per_sec
Symbol Float64 Float64 Float64 Float64 Float64 Float64 Float64
y[12] 0.0004 0.0006 0.0000 0.0000 815.1909 1.0082 0.4020
y[13] 0.0004 0.0007 0.0000 0.0000 684.4333 1.0042 0.3375
y[14] 0.0005 0.0008 0.0000 0.0000 667.7636 1.0055 0.3293
y[15] 0.0008 0.0010 0.0000 0.0000 703.1255 1.0026 0.3467
y[16] 0.0016 0.0015 0.0000 0.0000 611.2506 1.0052 0.3014
y[17] 0.0028 0.0022 0.0000 0.0001 501.4286 1.0057 0.2473
y[18] 0.0036 0.0027 0.0000 0.0001 459.1139 1.0063 0.2264
y[19] 0.0027 0.0022 0.0000 0.0001 488.3284 1.0078 0.2408
y[20] 0.0067 0.0045 0.0000 0.0002 397.7043 1.0122 0.1961
y[21] 0.0106 0.0068 0.0000 0.0003 348.9909 1.0176 0.1721
y[22] 0.0133 0.0082 0.0000 0.0003 340.5442 1.0195 0.1679
y[23] 0.0130 0.0079 0.0000 0.0003 342.7045 1.0200 0.1690
y[24] 0.0100 0.0063 0.0000 0.0003 362.7006 1.0188 0.1789
y[25] 0.0067 0.0045 0.0000 0.0002 400.3231 1.0165 0.1974
y[26] 0.0054 0.0038 0.0000 0.0001 392.4336 1.0165 0.1935
y[27] 0.0046 0.0033 0.0000 0.0001 425.4097 1.0128 0.2098
y[28] 0.0030 0.0024 0.0000 0.0001 446.8808 1.0130 0.2204
⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
24 rows omitted
Quantiles
parameters 2.5% 25.0% 50.0% 75.0% 97.5%
Symbol Float64 Float64 Float64 Float64 Float64
y[12] 0.0000 0.0000 0.0001 0.0005 0.0021
y[13] 0.0000 0.0000 0.0001 0.0005 0.0023
y[14] 0.0000 0.0000 0.0002 0.0007 0.0027
y[15] 0.0000 0.0001 0.0005 0.0012 0.0035
y[16] 0.0000 0.0005 0.0012 0.0022 0.0054
y[17] 0.0000 0.0011 0.0023 0.0038 0.0084
y[18] 0.0001 0.0016 0.0030 0.0049 0.0105
y[19] 0.0000 0.0011 0.0022 0.0038 0.0083
y[20] 0.0001 0.0035 0.0058 0.0088 0.0177
y[21] 0.0001 0.0061 0.0095 0.0139 0.0271
y[22] 0.0004 0.0078 0.0120 0.0174 0.0328
y[23] 0.0004 0.0076 0.0117 0.0169 0.0317
y[24] 0.0002 0.0057 0.0089 0.0132 0.0250
y[25] 0.0001 0.0036 0.0060 0.0090 0.0177
y[26] 0.0000 0.0027 0.0048 0.0073 0.0144
y[27] 0.0001 0.0022 0.0040 0.0063 0.0127
y[28] 0.0000 0.0013 0.0025 0.0042 0.0091
I would like to extract the two dataframes: (1) the means of y[i] and (2) the quantiles of y[i]. I could do this manually but converting the chain object to a dataframe by DataFrame(chain) and then take the mean (and quantile) of eachcol but I was wondering if there was a way to just extract this data from the chain object.
And follow up question, how exactly do I check for MCMC convergence? I’d like to extract the data for the associated traceplots.