Function for plotting iterations of posterior distributions

Function for plotting iterations of posterior distributions

Usage

distributionPlot(
  fits,
  form,
  df,
  priors = NULL,
  params = NULL,
  maxTime = NULL,
  patch = TRUE,
  virOptions = c("plasma", "mako", "viridis", "cividis", "magma", "turbo", "inferno",
    "rocket")
)

Arguments

fits

A list of brmsfit objects following the same data over time. Currently checkpointing is not supported.

form

A formula describing the growth model similar to growthSS and brmPlot such as: outcome ~ predictor |individual/group

df

data used to fit models (this is used to plot each subject's trend line).

priors

a named list of samples from the prior distributions for each parameter in params. This is only used if sample_prior=FALSE in the brmsfit object. If left NULL then no prior is included.

params

a vector of parameters to include distribution plots of. Defaults to NULL which will use all parameters from the top level model. Note that these parameters have to be estimated per each group in the model, if you have interecept only terms (estimated once across all groups) then manually specify params to not include those.

maxTime

Optional parameter to designate a max time not observed in the models so far

patch

Logical, should a patchwork plot be returned or should lists of ggplots be returned?

virOptions

A vector of names or letters for which viridis maps to use for each group.

Value

A ggplot or a list of ggplots (depending on patch).

Examples

# \donttest{
f <- "https://raw.githubusercontent.com/joshqsumner/pcvrTestData/main/brmsFits.rdata"
tryCatch(
  {
    print(load(url(f)))
    library(brms)
    library(ggplot2)
    library(patchwork)
    fits <- list(fit_3, fit_15)
    form <- y~time | id / group
    priors <- list(
      "phi1" = rlnorm(2000, log(130), 0.25),
      "phi2" = rlnorm(2000, log(12), 0.25),
      "phi3" = rlnorm(2000, log(3), 0.25)
    )
    params <- c("A", "B", "C")
    d <- simdf
    maxTime <- NULL
    patch <- TRUE
    from3to25 <- list(
      fit_3, fit_5, fit_7, fit_9, fit_11,
      fit_13, fit_15, fit_17, fit_19, fit_21, fit_23, fit_25
    )
    distributionPlot(
      fits = from3to25, form = y ~ time | id / group,
      params = params, d = d, priors = priors, patch = FALSE
    )
    distributionPlot(
      fits = from3to25, form = y ~ time | id / group,
      params = params, d = d, patch = FALSE
    )
  },
  error = function(e) {
    message(e)
  }
)
#>  [1] "fit_3"  "fit_5"  "fit_7"  "fit_9"  "fit_11" "fit_13" "fit_15" "fit_17"
#>  [9] "fit_19" "fit_21" "fit_23" "fit_25" "simdf" 
#> Loading required package: Rcpp
#> Loading 'brms' package (version 2.22.0). Useful instructions
#> can be found by typing help('brms'). A more detailed introduction
#> to the package is available through vignette('brms_overview').
#> 
#> Attaching package: ‘brms’
#> The following object is masked from ‘package:stats’:
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# }
## End(Not run)