compute_quantiles_2 {MSinference} | R Documentation |
Computes quantiles of the gaussian multiscale statistics.
Description
Quantiles from the gaussian version of the test statistics which are used to approximate the critical values for the multiscale test.
Usage
compute_quantiles_2(
t_len,
n_ts = 1,
grid = NULL,
ijset = NULL,
sigma = 1,
deriv_order = 0,
sim_runs = 1000,
probs = seq(0.5, 0.995, by = 0.005),
correction = TRUE,
epidem = FALSE,
numCores = NULL
)
Arguments
t_len |
Sample size. |
n_ts |
Number of time series analyzed. Default is 1. |
grid |
Grid of location-bandwidth points as produced by
the function |
ijset |
A matrix of integers. In case of multiple time series,
we need to know which pairwise comparisons to perform.
This matrix consists of all pairs of indices |
sigma |
Value of |
deriv_order |
In case of a single time series analysed, this parameter denotes the order of the derivative of the trend function that is being estimated. Default is 0. |
sim_runs |
Number of simulation runs to produce quantiles. Default is 1000. |
probs |
A numeric vector of probability levels |
correction |
Logical variable, TRUE (by default) if we are using
|
epidem |
Logical variable, TRUE if we are using dealing with epidemic time trends. Default is FALSE. |
numCores |
Integer value used to indicate how many cores are used
while calculating the critical value. Default is NULL,
then the formula used is
|
Value
Matrix with 2 rows where the first row contains the vector of probabilities (probs) and the second contains corresponding quantiles of the gaussian statistics distribution.
Examples
compute_quantiles_2(100, numCores = 2)