Permutation Test: Transition Matrix

Monte Carlo resampling of a time series using a discretised version of y, a sequence of bin numbers with unique values equal to nbins:

1. The discrete version of y will be used to generate a transition matrix of size nbins X nbins.

2. This transition matrix will be used to resample values

Usage

ts_permtest_transmat(
  y1,
  y2 = NULL,
  targetValue = 0,
  nbins = ceiling(2 * length(y1)^(1/3)),
  Nperms = 19,
  alpha = 0.05,
  keepNA = TRUE
)

Arguments

y1

Time series 1. The goal of the permutation test will be to decide whether the difference y1-targetValue != 0 for each time point, given alpha.

y2

An optional second time series. If this timeseries is provided then the goal of the permutation test will be the to decide wether the difference y2-y1 != targetValue for each time point, given alpha.

targetValue

The target value for the permutation test. If NULL, the function will return a data frame with the block randomised surrogates columns (default = 0)

nbins

Number of bins to use (default = ceiling(2*length(y1)^(1/3)))

Nperms

Number of permutations (default = 19)

alpha

Alpha level for deciding significance (default = 0.05)

keepNA

keepNA

Value

Resampled series

See also

Other Time series operations: ts_center(), ts_changeindex(), ts_checkfix(), ts_detrend(), ts_diff(), ts_discrete(), ts_duration(), ts_embed(), ts_integrate(), ts_levels(), ts_peaks(), ts_permtest_block(), ts_rasterize(), ts_sd(), ts_slice(), ts_slopes(), ts_standardise(), ts_sumorder(), ts_symbolic(), ts_trimfill(), ts_windower()

Examples

set.seed(4321)
y <- rnorm(5000)
ts_permtest_transmat(y)
#>       rbin          ry
#>  [1,]   16  0.02075621
#>  [2,]   20  0.78987315
#>  [3,]   11 -1.14036837
#>  [4,]    9 -1.46663841
#>  [5,]   14 -0.38170474
#>  [6,]   17  0.13077913
#>  [7,]   22  1.21152759
#>  [8,]   11 -1.01566755
#>  [9,]   16  0.03722538
#> [10,]   17  0.28382814
#> [11,]   20  0.73169567
#> [12,]   12 -0.79037980
#> [13,]   13 -0.65595026
#> [14,]   12 -0.82335198
#> [15,]   19  0.67282503
#> [16,]   25  1.84039798
#> [17,]   15 -0.10940063
#> [18,]    7 -1.78496950
#> [19,]   19  0.70681715
#> [20,]   21  0.96253150
#> [21,]   22  1.31323045
#> [22,]   13 -0.69397775
#> [23,]   10 -1.22548324
#> [24,]   15 -0.25772863
#> [25,]   20  0.71951206
#> [26,]   21  0.93210270
#> [27,]   13 -0.66000699
#> [28,]    9 -1.41892332
#> [29,]   19  0.51425756
#> [30,]   24  1.73325662
#> [31,]   11 -0.99692179
#> [32,]   23  1.36824680
#> [33,]   18  0.33640892
#> [34,]   26  1.96289025
#> [35,]   26  2.01432372