plot.cytoeffect_poisson: Plot posterior summaries for Poisson log-normal mixed model

In ChristofSeiler/cytoeffect: Regression Models with Multivariate Outcomes for Mass Cytometry Experiments

Description

Plot posterior summaries for Poisson log-normal mixed model

Usage

## S3 method for class 'cytoeffect_poisson'
plot(x, type = "beta", selection = x$protein_names, ...)

Arguments

x	Object of class cytoeffect_poisson computed using poisson_lognormal
type	A string with the parameter to plot: type = "theta", type = "beta", type = "sigma", or type = "Cor"
selection	A vector of strings with a selection of protein names to plot
...	Other parameters

Value

ggplot2 object

Examples

set.seed(1)
df = simulate_data(n_cells = 10)
str(df)
fit = poisson_lognormal(df,
                        protein_names = names(df)[3:ncol(df)],
                        condition = "condition",
                        group = "donor",
                        r_donor = 2,
                        warmup = 200, iter = 325, adapt_delta = 0.95,
                        num_chains = 1)
plot(fit, type = "beta")

ChristofSeiler/cytoeffect documentation built on Nov. 24, 2020, 12:25 a.m.