I have daily rainfall data which I have converted to yearwise cumulative value using following code
library(tidyverse); library(segmented); library(seas); library(strucchange)
## get mscdata from "seas" packages
data(mscdata)
dat <- (mksub(mscdata, id=1108447))
## generate cumulative sum of rain by year
d2 <- dat %>% group_by(year) %>% mutate(rain_cs = cumsum(rain)) %>% ungroup
Then I want to compute of yearwise breakpoints using strucchange
. I could able to do it for single year like
y <- subset(d2,year=="1992")$rain_cs
breakpoints(y ~ 1, breaks = 3)$breakpoints
I have used breaks = 3
to have 3 breakpoints. Now how to dynamically apply it year-wise to estimate breakpoints?
You can group_by
year
and use summarise
in dplyr
1.0.0 which can generate multiple rows in summarise
:
library(dplyr)
library(strucchange)
d2 %>%
group_by(year) %>%
summarise(breakpoints = breakpoints(rain_cs~1, breaks = 3)$breakpoints)
# year breakpoints
# <int> <dbl>
# 1 1975 73
# 2 1975 237
# 3 1975 301
# 4 1976 83
# 5 1976 166
# 6 1976 297
# 7 1977 98
# 8 1977 239
# 9 1977 311
#10 1978 102
# … with 80 more rows
To get data as 3 columns instead, we can store the output in a list and use unnest_wider
.
d2 %>%
group_by(year) %>%
summarise(breakpoints = list(breakpoints(rain_cs~1,breaks = 3)$breakpoints)) %>%
tidyr::unnest_wider(breakpoints) %>%
tibble::column_to_rownames('year')
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