traceplot_array.RdMegaLMM parameters are all matrices. Parameters related to the factor loadings matrix
Lambda all have K rows. Factors related to the factor scores
all have K columns. Some parameters only have 1 row or column, but are still stored as matrices.
Posterior samples of these parameters are arrays with dimensions: Ixnxm for
I samples of a parameter with dimensions nxm.
traceplot_array(
sample_array,
facet_dim = 2,
name = "param",
n_per_facet = 5,
mask = NULL,
include_zero = TRUE
)Ixnxm array of posterior samples for a matrix of dimension nxm
either 2 or 3, giving the dimension of sample_array that should be used as the facets
string giving a name to assign to the plot. The file will be a pdf booklet stored in the `run_ID` folder with this name.
maximum number of values to make traces per facet
optional nxm logical matrix giving values of the parameter matrix that should NOT be plotted
should each facet include the value zero?
None
This function makes trace plots of parameters using a faceting scheme to try to
display as many parameter traces as possible in an organized way. In all plots,
the sample number will be the x-axis. The plot(s) will be divided into facets by either the
second (default) or 3rd dimension of the sample_array. Within a facet there will be
lines showing the traces of individual values within that dimension of the matrix.
In cases where the matrix is large in that dimension, only the n_per_facet
traces with the largest (absolute) posterior mean will be shown, as these are probably the
most important.
Sometimes (particularly in a cross-validation framework) we may have a matrix with
many parameters, but only some of them are interesting to inspect traces. You can supply
an nxm logical matrix mask where TRUE means the value will be masked
from the plot, and FALSE means the value will be plotted.
traceplot_array(load_posterior_param(MegaLMM_state,'Lambda'),2,'Lambda')
#> Error in load_posterior_param(MegaLMM_state, "Lambda"): object 'MegaLMM_state' not found