est_edd_all_methods: Estimates the edd for a given change for all methods.
In Tveten/tpcaMonitoring: Simulation Study for Changepoint Detection by TPCA.

Description Usage Arguments Details

Description

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est_edd_all_methods(train_obj, n_max, n_sim, edd_file, kappa, p, w, p0s,
  r_pca, threshold_settings, mu = NULL, sigma = NULL,
  rho_scale = NULL)

`train_obj`	A list returned from `get_training_sets`.
`n_max`	The maximum number of monitoring samples.
`n_sim`	The number of run length simulations to estimate the EDD.
`edd_file`	A string specifying the file to print results to.
`kappa`	The change-point.
`p`	A number between 0 and 1. The proportion of affected streams.
`w`	The window length.
`p0s`	A vector of p0-values to be used in the mixture procedure.
`r_pca`	A vector of the numbers of projections to keep in Max and Min PCA.
`threshold_settings`	A list with named elements 'n' and 'alpha', giving the settings used to control the probability of false alarm.
`mu`	A numeric specifying the change in mean.
`sigma`	A numeric specifying the change in standard deviation.
`rho_scale`	A numeric specifying the change in correlation.

Simulates n_sim run lengths and calculates the EDD for all methods (Mixture, Min PCA, Max PCA and TPCA) together with other summary statistics of the run length distribution. These values are not returned, but printed to the input edd_file. The input kappa, p, mu, sigma and rho_scale constitute the change scenario to estimate the EDD for. p0s is a vector of parameters for the the mixture procedure, while r_pca is a vector of the number of projections to retain in Max and Min PCA. The chosen projections for TPCA is found from the file axes-file created during the threshold-finding phase.