DistributionApproximation {emcAdr} | R Documentation |
The MCMC method that runs the random walk on a single cocktail in order to estimate the distribution of score among cocktails of size Smax.
Description
The MCMC method that runs the random walk on a single cocktail in order to estimate the distribution of score among cocktails of size Smax.
Usage
DistributionApproximation(
epochs,
ATCtree,
observations,
temperature = 1L,
nbResults = 5L,
Smax = 2L,
p_type1 = 0.01,
beta = 4L,
max_score = 500L,
num_thread = 1L,
verbose = FALSE
)
Arguments
epochs |
: number of steps for the MCMC algorithm |
ATCtree |
: ATC tree with upper bound of the DFS (without the root, also see on the github repo for an example) |
observations |
: real observation of the AE based on the medications of each patients (a DataFrame containing the medication on the first column and the ADR (boolean) on the second) |
temperature |
: starting temperature, default = 1 (denoted T in the article) |
nbResults |
: Number of returned solution (Cocktail of size Smax with the best oberved score during the run), 5 by default |
Smax |
: Size of the cocktail we approximate the distribution from |
p_type1 |
: probability to operate type1 mutation. Note : the probability to operate the type 2 mutation is then 1 - P_type1. P_type1 must be in [0;1]. Default is .01 |
beta |
: filter the minimum number of patients that must have taken the cocktail for his risk to be taken into account in the DistributionScoreBeta default is 4 |
max_score |
: maximum number the score can take. Score greater than this one would be added to the distribution as the value max_score. Default is 500 |
num_thread |
: Number of thread to run in parallel if openMP is available, 1 by default |
verbose |
: Output summary (default is false) |
Value
I no problem, return a List containing : - ScoreDistribution : the distribution of the score as an array with each cells representing the number of risks = (index-1)/ 10 - Outstanding_score : An array of the score greater than max_score, - Best_cocktails : the nbResults bests cocktails encountered during the run. - Best_scores : Score corresponding to the bestCocktails. - FilteredDistribution : Distribution containing score for cocktails taken by at least beta patients. - Best_cocktails_beta : the nbResults bests cocktails taken by at least beta patients encountered during the run. - Best_scores_beta : Score corresponding to the bestCocktailsBeta. - cocktailSize : Smax parameter used during the run. ; Otherwise the list is empty
Examples
data("ATC_Tree_UpperBound_2024")
data("FAERS_myopathy")
estimation = DistributionApproximation(epochs = 10, ATCtree = ATC_Tree_UpperBound_2024,
observations = FAERS_myopathy)