Description Details Author(s) References Examples

Monte Carlo tests for weak signals in time-series

This package provides the functions `randomThinningTest`

(which
performs the test in question), `calculateTSstatistics`

(which
calculates relevant properties of the time-series),
`calculatePower`

(which estimates the power of the test for a
given data-set) and `rangeTest`

(the statistic underlying these
tests).

Jeremy Silver [email protected]

These tests first appeared in Earl et al. 2015:

Earl, N., Simmonds, I. & Tapper, N. (2015) Weekly cycles of global fires - Associations with religion, wealth and culture, and insights into anthropogenic influences on global climate. Geophysical Research Letters. 42 (21): 9579–9589

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
## Generate a random time-series:
## - length = 1000
## - signal period = 8
## - signal to noise ratio = 0.2
set.seed(42)
x <- rep(rnorm(8)*0.2,length.out = 1000) + rnorm(1000)
randomThinningTest(ts = x, p = 8, n = 1000,
fr = 0.025, returnExtraInfo = TRUE)
## compare with periods either too short or too long:
randomThinningTest(ts = x, p = 7, n = 1000, fr = 0.025)
randomThinningTest(ts = x, p = 9, n = 1000, fr = 0.025)
``` |

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