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# Loading necessary libraries
library(ggplot2)
library(tidyverse)
## -- Attaching core tidyverse packages ------------------------ tidyverse 2.0.0 --
## v dplyr 1.1.3 v readr 2.1.4
## v forcats 1.0.0 v stringr 1.5.0
## v lubridate 1.9.3 v tibble 3.2.1
## v purrr 1.0.2 v tidyr 1.3.0
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
## i Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(readr)
library(xts)
## Loading required package: zoo
##
## Attaching package: 'zoo'
##
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
##
##
## ######################### Warning from 'xts' package ##########################
## # #
## # The dplyr lag() function breaks how base R's lag() function is supposed to #
## # work, which breaks lag(my_xts). Calls to lag(my_xts) that you type or #
## # source() into this session won't work correctly. #
## # #
## # Use stats::lag() to make sure you're not using dplyr::lag(), or you can add #
## # conflictRules('dplyr', exclude = 'lag') to your .Rprofile to stop #
## # dplyr from breaking base R's lag() function. #
## # #
## # Code in packages is not affected. It's protected by R's namespace mechanism #
## # Set `options(xts.warn_dplyr_breaks_lag = FALSE)` to suppress this warning. #
## # #
## ###############################################################################
##
## Attaching package: 'xts'
##
## The following objects are masked from 'package:dplyr':
##
## first, last
library(corrplot)
## corrplot 0.92 loaded
library(vars)
## Loading required package: MASS
##
## Attaching package: 'MASS'
##
## The following object is masked from 'package:dplyr':
##
## select
##
## Loading required package: strucchange
## Loading required package: sandwich
##
## Attaching package: 'strucchange'
##
## The following object is masked from 'package:stringr':
##
## boundary
##
## Loading required package: urca
## Loading required package: lmtest
# Load rainfall dataset
data <- read_csv("~/Rainfall.csv")
## Rows: 61 Columns: 7
## -- Column specification --------------------------------------------------------
## Delimiter: ","
## dbl (7): Year, VRY, KRI, BLO, BET, ERM, POT
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
# convert the "Date" column to a proper date format
data_ts <- xts(data[, -1], order.by = as.yearmon(data$Year, format = "%Y"))
```
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