plot_levels_hier_mixG: Plot kernel density of samples in hierarchical tree
In rchan26/mixGaussTempering: What the Package Does (One Line, Title Case)

Description Usage Arguments Value Examples

This function plots the kernel densities of the samples in the hierarchical tree (in red) and the tempered target densities that they were targetting (in blue)

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plot_levels_hier_mixG(hier_result, weights, means, sds, from, to,
  plot_rows, plot_columns, whole = F, bw = rep("nrd0",
  length(hier_result$samples)))

`hier_result`	hierarchical Monte Carlo fusion result
`from, to`	the range over which the function will be plotted: integer (if want to have it constant throughout) or vector of length L, where L is the number of levels in the hierarchy
`plot_rows`	number of rows in plot (should make is so plot_rows x plot_columns = L)
`plot_columns`	number of rows in plot (should make is so plot_rows x plot_columns = L)
`whole`	boolean value: defaults to F, determines whether or not to plot kde for all samples in the level or for each node (T)
`bw`	the smoothing bandwidth used: integer (if want to have it constant throughout) or vector of length L, where L is the number of levels in the hierarchy

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# setting variables
w_example <- c(0.35, 0.65)
m_example <- c(-3, 8)
s_example <- c(1, 1.5)
b_example <- 1/4

# sampling from tempered density
nsamples <- 500000
base <- hmc_base_sampler_mixG(w_example, m_example, s_example, b_example, nsamples, 4)

test <- parallel_h_fusion_TA_mixG(N_schedule = rep(10000, 2), time_schedule = 1,
                                  start_beta = b_example, C_schedule = rep(2, 2), L = 3, base_samples = base,
                                  weights = w_example, means = m_example, sds = s_example, study = T)

# plot results with constant from and to
plot_levels_hier_mixG(test, weights = w_example, means = m_example, sds = s_example,
                      from = -15, to = 20, plot_rows = 3, plot_columns = 1)

# plot results with specified bandwidths
plot_levels_hier_mixG(test, weights = w_example, means = m_example, sds = s_example,
                      from = -15, to = 20, plot_rows = 3, plot_columns = 1, bw = c(0.2, 0.3, 0.4))