Simulate a Time Series
sim_ts.Rd
sim_ts()
is mostly a helper function, to be used
internally in this package, but you can use it here to simulate a time series.
Arguments
- n
a numeric vector for the length of the series
- b0
a numeric vector for a potential drift in the series. Defaults to 0
- bt
a numeric vector for a potential trend in the series. Defaults to 0.
- rho
a numeric vector for the simple autoregressive parameter. Defaults to 1.
- white_noise
= logical, defaults to FALSE. If FALSE, generates a random walk. If TRUE, series is white noise.
- rsd
the standard deviation for a normal distribution to be simulated. Defaults to 1.
Value
sim_ts()
returns a numeric vector of a simulated time series
that would follow the user's input.
Examples
set.seed(8675309) # don't want new numbers in documentation every time...
sim_ts(25)
#> [1] -0.9965824 -0.2747582 -0.8919670 1.1374246 2.2028406 3.1900603
#> [7] 3.2175143 3.8903866 4.4624531 5.3661308 3.8165784 4.8392162
#> [13] 4.9892994 4.3293354 3.3347464 5.3072051 4.8654034 3.9647662
#> [19] 3.8141780 2.9862838 4.9721096 5.0161147 4.6118324 4.1388338
#> [25] 3.7240106
sim_ts(25, b0 = 1)
#> [1] 1.683234 3.373435 4.906927 5.720822 7.103768 8.479952 10.633483
#> [8] 13.208385 14.796913 15.181867 15.952956 17.016873 17.703400 18.454900
#> [15] 19.301105 19.665848 20.662054 21.707669 23.391741 24.139698 24.988660
#> [22] 25.113728 24.136827 25.374490 26.410581
sim_ts(25, b0 = 1, bt = .05)
#> [1] 1.184898 2.352480 2.576891 1.491655 2.755863 2.858795 3.257155
#> [8] 5.035858 7.135636 8.287603 10.934595 12.548679 13.443317 13.317850
#> [15] 14.225703 16.176485 17.584662 17.716140 17.444117 18.721917 19.424063
#> [22] 21.774787 22.600140 21.053274 21.181542