Time Series King’s Death

Time Series Analysis for King’s Death Data

By EOH Geng

Load neccessary library

library(haven)
library(here)

here() starts at C:/Users/User/Desktop/DrPH/ENV EPID & SUSTAINABILITY/time series

library(ggplot2)
library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.1     ✔ stringr   1.5.2
✔ lubridate 1.9.4     ✔ tibble    3.3.0
✔ purrr     1.1.0     ✔ tidyr     1.3.1

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(lubridate)
library(TTR)
library(forecast)

Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 

Load the data

kings<-scan("http://robjhyndman.com/tsdldata/misc/kings.dat",skip=3)
kings

 [1] 60 43 67 50 56 42 50 65 68 43 65 34 47 34 49 41 13 35 53 56 16 43 69 59 48
[26] 59 86 55 68 51 33 49 67 77 81 67 71 81 68 70 77 56

Convert the data to a time series object

kingstimeseries<-ts(kings)
kingstimeseries

Time Series:
Start = 1 
End = 42 
Frequency = 1 
 [1] 60 43 67 50 56 42 50 65 68 43 65 34 47 34 49 41 13 35 53 56 16 43 69 59 48
[26] 59 86 55 68 51 33 49 67 77 81 67 71 81 68 70 77 56

Plot the time series data

plot.ts(kingstimeseries)

Decomposing Time Series by smoothing non-seasonal data

Setting moving average 3

kingstimeseriesSMA3 <- SMA(kingstimeseries,n=3)
plot.ts(kingstimeseriesSMA3)

Setting moving average 8

kingstimeseriesSMA8 <- SMA(kingstimeseries,n=8)
plot.ts(kingstimeseriesSMA8)

Khalasss. Syukran