simulate data from a second order random walk

simulate data from a second order random walk

simulate_rw(sigma = NULL, tau = NULL, length = 10, start = 1,
  order = 1, n_sim = 1000)

Arguments

sigma	the standard deviation of the random walk process
tau	the precision of the random walk process
length	the length of the time series
start	the starting values of the time series
order	1 for first order random walk or 2 for second order random walk
n_sim	the number of simulations

Value

a data.frame with simulated time series from the random walk

See also

Other priors: plot.sim_iid, plot.sim_rw, select_change, select_divergence, select_poly, select_quantile, simulate_iid

Examples

set.seed(20181202)
x <- simulate_rw(sigma = 0.1, start = -10, length = 40)
head(x)
#> # A tibble: 6 x 3
#>       x       y replicate
#>   <dbl>   <dbl>     <int>
#> 1   -10  0              1
#> 2    -9 -0.0770         1
#> 3    -8 -0.313          1
#> 4    -7 -0.560          1
#> 5    -6 -0.634          1
#> 6    -5 -0.688          1
y <- simulate_rw(sigma = 0.001, start = -10, length = 40, order = 2)
head(y)
#> # A tibble: 6 x 3
#>       x         y replicate
#>   <dbl>     <dbl>     <int>
#> 1   -10  0                1
#> 2    -9  0                1
#> 3    -8 -0.000880         1
#> 4    -7 -0.00264          1
#> 5    -6 -0.00397          1
#> 6    -5 -0.00490          1