ncdDetect: Add discrete stochastic random variables of same dimension
In MaleneJuul/ncdDetectTools: Functions to perform convolution

Description Usage Arguments Value Examples

Add discrete stochastic random variables of same dimension

1	ncdDetect(predictions, scores, observations = NA, thres = NA)

`predictions`	A matrix in which each row corresponds to a discrete random variable and each column corresponds to a discrete outcome. The matrix contains the probabilities of each outcome, and each row must sum to one.
`scores`	A matrix in which each row corresponds to a discrete random variable and each column corresponds to a discrete outcome. The matrix contains the values for each outcome for each random variable.
`observations`	A matrix (optional) in which each row corresponds to a discrete random variable and each column corresponds to a discrete outcome. The matrix contains the observed outcome for each variable. Each row must contain exactly one 1, while the rest of the entries must be 0.
`thres`	An optional number to set a threshold. If set, the probabilities of all possible outcomes of the sum of the random variables are only caluclated below this value.

score_dist The convoluted distribution of the sum of the discrete random variables defined by input matrices predictions and scores.

obs_score The observed score. Only returned if matrix observations is provided as input.

p_value The p-value resulting from evaluating the observed score in the convoluted distribution. Only returned if matrix observations is provided as input.

ncdDetect(predictions = matrix(rep(1/6, 12), nrow = 2), scores = matrix(rep(1:6, 2), nrow = 2, byrow = TRUE), 
    observations = matrix(c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0), nrow = 2, byrow = TRUE))
ncdDetect(predictions = matrix(rep(1/6, 12), nrow = 2), scores = matrix(rep(1:6, 2), nrow = 2, byrow = TRUE), thres = 6)
ncdDetect(predictions = matrix(rep(1/6, 12), nrow = 2), scores = matrix(rep(1:6, 2), nrow = 2, byrow = TRUE))