R 如何创建一个依赖于先前观察到的事件平均值的列

您可以在dplyr中使用lag、rowwise*和mutate:

library(dplyr)

df |>
  mutate(gdp3_growth_lag1 = lag(gdp_growth, 1),
         gdp3_growth_lag2 = lag(gdp_growth, 2),
         gdp3_growth_lag3 = lag(gdp_growth, 3)) |>
  rowwise() |>
    mutate(
      gdp3_growth_mean = mean(c_across(starts_with("gdp3_growth_lag"))),
      gdp3_growth_sd = sd(c_across(starts_with("gdp3_growth_lag")))
    ) |>
  ungroup() |>
  mutate(crisis = case_when(gdp_growth <= gdp3_growth_mean - 2 * gdp3_growth_sd ~ 2,
                            gdp_growth <= gdp3_growth_mean - gdp3_growth_sd ~ 1,
                            is.na(gdp3_growth_mean) ~ NA_real_,
                            TRUE ~ 0)) |>
  select(-starts_with("gdp3"))

Output:

# A tibble: 33 × 3
   gdp_growth  year crisis
        <dbl> <dbl>  <dbl>
 1          5  1990     NA
 2          4  1991     NA
 3          0  1992     NA
 4         -4  1993      2
 5         -3  1994      0
 6         -1  1995      0
 7          2  1996      0
 8          4  1997      0
 9          7  1998      0
10         10  1999      0
11          8  2000      0
12        -10  2001      2
13         -8  2002      0
14          2  2003      0
15          4  2004      0
16          5  2005      0
17          8  2006      0
18          4  2007      0
19        -10  2008      2
20         -9  2009      1
21         -8  2010      0
22         -3  2011      0
23          0  2012      0
24         -5  2013      0
25         -6  2014      1
26         -2  2015      0
27          4  2016      0
28          5  2017      0
29          5  2018      0
30          8  2019      0
31          2  2020      2
32         -1  2021      2
33         -1  2022      0

Updated with full output.

(*)matrixStats中也有rowSds