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Obtain posterior probability of being a signal

Source: R/pvEBayes_object_S3_methods.R
get_posterior_prob.Rd

Obtain posterior probability of being a signal

Usage

get_posterior_prob(obj, cutoff_signal = 1.001)

Arguments

obj

a pvEBayes object, which is the output of the function pvEBayes or pvEBayes_tune.

cutoff_signal

numeric. Threshold for signal detection. An AE-drug combination is classified as a detected signal if its 5th posterior percentile exceeds this threshold.

Value

a matrix

Examples


fit <- pvEBayes(
  contin_table = statin2025_44, model = "general-gamma",
  alpha = 0.3, n_posterior_draws = 1000
)
#> ℹ Fitting general-gamma model...
#> ✔ Fitting general-gamma model... [214ms]
#> 
#> ℹ Generating 1000 posterior draws...
#> ✔ Generating 1000 posterior draws... [35ms]
#> 
#> Object of class 'pvEBayes'
#> 
#> General-gamma model with hyperparameter alpha = 0.3.
#> Estimated prior is a mixture of 18 gamma distributions.
#> 
#> Running time of the general-gamma model fitting: 0.2213 seconds.
#> Optimizer convergence: successful.
#> Running time for posterior draws 
#> (1000 signal strength posterior draws per AE-drug pair):0.0425 seconds.
#> 
#> Extract estimated prior parameters, discovered signals
#> and signal strength posterior draws using `summary()`.

posterior_probs <- get_posterior_prob(fit,
cutoff_signal = 1.001)