exuber
Simulation
Simulation of a bivariate co-explosive pair
sim_coexplosive sim_coexplosive(
n,
lag = 0,
phi_x = 1,
phi_z = 0,
mu_y = 0,
sigma_y = 6.79,
x_args = list(),
z_args = list(),
seed = NULL
)Simulates the co-explosive process of Evripidou, Harvey, Leybourne & Sollis (2022): an explosive series x (from sim_psy1) and a second series y that is linked to a lead or lagged copy of it, and optionally to a third, independent explosive series z, . i > 0 means that the explosive episode of x leads that of y, and i < 0 means that it lags.
Arguments
| n | A positive integer specifying the length of the simulated output series. |
| lag | Integer lead (> 0) or lag (< 0) of x relative to y; 0 = contemporaneous. |
| phi_x, phi_z, mu_y | Linkage coefficients and intercept for y. |
| sigma_y | A non-negative scalar, the standard deviation of y's own noise. |
| x_args, z_args | Named lists of extra arguments passed to the sim_psy1 calls generating x and (if phi_z != 0) z. |
| seed | An object specifying if and how the random number generator (rng)
should be initialized. It is either NULL or an integer, which is passed to
set.seed before the simulation. If you set it, the value is saved as the
"seed" attribute of the returned value. The default, NULL, leaves the state of
the rng unchanged and returns .Random.seed as the "seed" attribute. Results are
reproducible across the parallel and the non-parallel option when you use the
same seed. |
Value
A data.frame with columns x and y (length n).
Examples
These examples are copied from the package's own documentation and are run by R CMD check on every release.
The printed output (after #>) and the plots were produced by running them against the current package source.
x <- sim_coexplosive(n = 100, lag = 5, seed = 123)
x
#> x y
#> 1 100.00000 NA
#> 2 96.19437 NA
#> 3 94.63147 NA
#> 4 105.21509 NA
#> 5 105.69385 NA
#> 6 106.57171 93.53851
#> 7 118.21700 95.88863
#> 8 121.34662 89.30196
#> 9 112.75686 93.88977
#> 10 108.09313 103.11211
#> 11 105.06708 112.81170
#> 12 113.37860 114.31040
#> 13 115.82173 125.47470
#> 14 118.54297 101.77143
#> 15 119.29451 107.71586
#> 16 115.52035 108.59386
#> 17 127.65349 115.42343
#> 18 131.03389 116.53927
#> 19 117.68056 114.19258
#> 20 122.44277 113.52501
#> 21 119.23251 108.56651
#> 22 111.98199 128.45231
#> 23 110.50194 124.60054
#> 24 103.53537 114.34967
#> 25 98.58620 120.70390
#> 26 94.34218 131.75234
#> 27 82.88953 107.55525
#> 28 88.57811 112.10021
#> 29 89.61951 104.06472
#> 30 81.89156 92.05519
#> 31 90.40496 93.85800
#> 32 93.30066 92.69803
#> 33 91.29712 91.64382
#> 34 97.37502 89.89948
#> 35 103.33755 79.02281
#> 36 108.91609 76.46342
#> 37 113.59195 100.98244
#> 38 117.35305 81.37938
#> 39 116.93267 102.39927
#> 40 122.23314 116.30036
#> 41 127.36213 99.11205
#> 42 130.68108 118.35707
#> 43 137.51474 115.57273
#> 44 137.59929 106.25782
#> 45 161.00843 111.94855
#> 46 179.36944 116.48770
#> 47 183.06098 127.07622
#> 48 191.87576 127.58942
#> 49 200.81371 142.27025
#> 50 218.78016 175.26817
#> 51 232.01818 170.63050
#> 52 248.37757 188.40972
#> 53 263.85530 197.09755
#> 54 280.21236 203.06936
#> 55 307.18537 211.93328
#> 56 120.70016 231.20710
#> 57 130.99699 246.47369
#> 58 120.48096 267.67800
#> 59 124.45049 277.68350
#> 60 125.29146 313.81902
#> 61 126.75770 118.15675
#> 62 129.33545 138.14490
#> 63 125.92468 113.35705
#> 64 123.66220 115.89403
#> 65 116.74607 147.29812
#> 66 109.46861 123.92724
#> 67 111.52957 131.36042
#> 68 114.57291 130.24698
#> 69 114.93281 120.37733
#> 70 121.19501 120.25556
#> 71 135.11508 111.97388
#> 72 131.78098 110.06713
#> 73 116.10172 115.01625
#> 74 122.93069 114.70150
#> 75 118.11522 135.64720
#> 76 113.44364 130.08141
#> 77 120.40727 124.33917
#> 78 118.47366 116.35831
#> 79 110.18499 125.03885
#> 80 111.41604 121.07921
#> 81 110.47296 110.33134
#> 82 110.51210 113.18728
#> 83 113.12816 127.05069
#> 84 110.61137 107.81086
#> 85 114.98669 105.53920
#> 86 113.48959 108.86863
#> 87 115.74239 109.17328
#> 88 123.18992 120.66451
#> 89 126.14481 111.18674
#> 90 123.93173 120.10672
#> 91 131.73213 110.09939
#> 92 138.47803 117.19847
#> 93 142.20164 120.98531
#> 94 143.82263 126.78703
#> 95 139.55915 117.85221
#> 96 148.79798 122.83179
#> 97 144.72221 152.03910
#> 98 159.57421 146.28045
#> 99 169.98063 135.32650
#> 100 168.38023 135.40933
# x's explosive episode should visibly lead y's by 5 periods
matplot(x, type = "l", lty = 1, col = c("steelblue", "tomato"),
xlab = "t", ylab = "value", main = "sim_coexplosive(): x leads y by 5 periods")
legend("topleft", legend = c("x", "y"), col = c("steelblue", "tomato"),
lty = 1, bty = "n")
See also
References
Evripidou, C., Harvey, D.I., Leybourne, S.J. & Sollis, R. (2022). "Co-explosive behaviour in explosive financial bubbles." OBES.