compute_statistics: Calculates the value of the test statistics both for single...
In MSinference: Multiscale Inference for Nonparametric Time Trend(s)

compute_statistics

R Documentation

Calculates the value of the test statistics both for single time series analysis and multiple time series analysis.

Calculates the value of the test statistics both for single time series analysis and multiple time series analysis.

compute_statistics(
  data,
  sigma = 1,
  sigma_vec = 1,
  n_ts = 1,
  grid = NULL,
  ijset = NULL,
  deriv_order = 0,
  epidem = FALSE
)

`data`	Vector (in case of n_ts = 1) or matrix (in case of n_ts > 1) that contains (a number of) time series that needs to be analyzed. In the latter case, each column of the matrix must contain one time series.
`sigma`	The estimator of the square root of the long-run variance `\sigma` in case of n_ts = 1, or the estimator of the overdispersion parameter `\sigma` in case of n_ts > 1 and epidemic = TRUE.
`sigma_vec`	Vector that consists of estimators of the square root of the long-run variances `\sigma_i` in case of n_ts > 1 and epidemic = FALSE.
`n_ts`	Number of time series analysed. Default is 1.
`grid`	Grid of location-bandwidth points as produced by the functions `construct_grid` or `construct_weekly_grid`, it is a list with the elements 'gset', 'bws', 'gtype'. If not provided, then the defalt grid is used. For the construction of the default grid, see `construct_grid`.
`ijset`	In case of multiple time series (n_ts > 1), we need to know which pairs of time series to compare. This matrix consists of all pairs of indices `(i, j)` that we want to compare. If not provided, then all possible pairwise comparison are performed.
`deriv_order`	In case of a single time series, this denotes the order of the derivative of the trend that we estimate. Default is 0.
`epidem`	Logical variable, TRUE if we are using dealing with epidemic time trends. Default is FALSE.

In case of n_ts = 1, the function returns a list with the following elements:

`stat`	Value of the multiscale statistics.
`gset_with_vals`	A matrix that contains the values of the normalised kernel averages for each pair of location-bandwidth with the corresponding location and bandwidth.

In case of n_ts > 1, the function returns a list with the following elements:

`stat`	Value of the multiscale statistics.
`stat_pairwise`	Matrix of the values of the pairwise statistics.
`ijset`	The matrix that consists of all pairs of indices `(i, j)` that we compared. The order of these pairs corresponds to the order in the list gset_with_vals.
`gset_with_vals`	A list of matrices, each matrix corresponding to a specific pairwise comparison. The order of the list is determined by ijset. Each matrix contains the values of the normalisedkernel averages for each pair of location-bandwidth with the corresponding location and bandwidth.