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exuber

Helpers

Helper function to find tb from Phillips and Shi (2020)

ps_tb
ps_tb(n, freq = c("monthly", "quarterly", "annual", "weekly"), size = 2)

This function finds the number of observations in the window over which size is to be controlled.

Arguments

n A positive integer. The sample size.
freq The type of date-interval.
size The size to be controlled.

Value

A single integer, the length of the training window in observations, suitable for the r_star argument of monitor.

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.

# Training window that controls size over a 2-year span of monthly data
tb <- ps_tb(100, freq = "monthly", size = 2)
tb
#> [1] 42

# Use it directly as the training window of monitor()
monitor(sim_data, r_star = tb, boundary = "kurozumi")
#> 
#> ── monitor (T* = 42 / 100, minw = 19, sig_lvl = 95%, boundary = kurozumi) ──────
#> 
#>   series  boundary  alarm  alarm_date
#>     psy1     1.038     50          50
#>     psy2     1.038     NA        <NA>
#>    evans     1.038     NA        <NA>
#>      div     1.038     NA        <NA>
#>     blan     1.038     NA        <NA>

References

Phillips, P. C., & Shi, S. (2020). Real time monitoring of asset markets: Bubbles and crises. In Handbook of Statistics (Vol. 42, pp. 61-80). Elsevier.

Shi, S., Hurn, S., Phillips, P.C.B., 2018. Causal change detection in possibly integrated systems: Revisiting the money-income relationship.