classInput: Inputs results into S4 class
In grundy95/changepoint.cov: Implementation of Covariance Changepoint Methods

Description Usage Arguments Value See Also

Function for inputting results into the S4 class cptCovariance.

classInput(
  X,
  cpts,
  method,
  numCpts,
  cptsSig,
  threshold,
  thresholdValue,
  msl,
  subspaceDim = 0,
  nperm = 0,
  LRCov = "NA"
)

`X`	Data matrix of dimension n by p.
`cpts`	Vector of changepoint locations
`method`	Covariance changepoint method to be used. Choice of "Ratio" or "CUSUM".
`numCpts`	Number of changepoints in the data. Choices include: "AMOC" - At Most One Changepoint; test to see if the data contains a single changepoint or not. "BinSeg"- Binary segmentation is performed to detect multiple changepoints. Numeric - User specified number of changepoints.
`cptsSig`	Data frame containing the changepoint locations along with their associated test statistics; threshold; and whether or not they were deemed significant
`threshold`	Threshold choice for determining significance of changepoints. Choices include: "Asymptotic" - Uses the asymptotic threshold derived for each method. For Ratio method the threshold is log(n). For CUSUM method the threshold is the specified quantile of the standard Normal distribution. The quantile is set by the argument thresholdValue. "Manual"- A user chosen threshold which is contained in the thresholdValue argument. NOTE the normalized test statistics will be compared to the set thresholds - see details for more information. If numCpts is numeric then the threshold is not used as the number of changepoints is known.
`thresholdValue`	Either the manual threshold value when threshold="Manual" or the (1-thresholdValue)-quantile of asymptotic distribution of the test statistic when threshold="Asymptotic".
`msl`	Minimum segment length allowed between the changepoints. NOTE this should be greater than or equal to p, the dimension of the time series.
`subspaceDim`	Dimension of the latent subspace.
`nperm`	Only required for threshold="PermTest". Number of permutations to use in the permutation test.
`LRCov`	The long-run covariance estimator to be used for CUSUM method. Currently, only "Bartlett" and "Empirical" are supported. Alternatively, a matrix containing the long-run covariance estimate can be inputted.