I have data of total exports of fish from my country in the time period 2010-2020. Since our currency (NOK) has gotten weaker to the currencies we are trading with, we have gotten a lot more value from our exports the last decade.
I have made data who shows how much we have earned from every month the last year. To get precise data for further analysis, I have taken the total value from our exports and divided it by the quantity we have exported.
I want to remove the seasonality of the data. For an example, we will export more every october then january.
This is what I have done:
library(rio) library(ggplot2) library(forecast) library(tseries) library(tidyverse) library(zoo)
VM = value/quantity of our exports
data_ma = ts(na.omit(data$VM), frequency = 12) decomp = stl(data_ma, "periodic") deseasonal_cnt <- seasadj(decomp) plot(decomp)
adf.test(data_ma, alternative = "stationary")
Result shows p-value at 0.04
Acf(data_ma, main = '')
Pacf(VM_ma, main = '')
I now want to remove the seasonality, but the I dont know what to do with the ACF and PACF tests as there is so much lags. Can someone please help?