BFF_poisson_seq_initial | R Documentation |
Detects change points within data stream sequentially using a Bayesian adaptive estimation procedure and predictive posterior p-values. Additionally estimates parameters
BFF_poisson_seq_initial( data, threshold_val = c(0.05), burnin = 200, grace_period = 20, sw = 2000, alpha = 39, beta = 1.8, post_p = TRUE, pred_p = TRUE )
data |
data stream to perform change point detection on |
threshold_val |
vector of thresholds to use to assess whether new data point is a change point |
burnin |
the intial period to use to build the model on which no change points are detected |
grace_period |
period after a change in which changes are not detected |
sw |
sliding window size for p-value calibration |
alpha |
alpha parameter for lambda beta prior |
beta |
beta parameter for lambda beta prior |
param_est |
whether to estimate paramters |
return the change points detected by the algorithm for each of the dection procedures, for the different thresholds. Collects p-values and model parameter estimates.
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