simulate data from a second order random walk

Source: R/simulate_rw.R

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