Times Series
Nana Frimpong
2025-02-05
#Chapter 2 Readings {r}# install.packages("fpp3")
2.1 tsiblle objetcs
library("fpp3")## Registered S3 method overwritten by 'tsibble':
## method from
## as_tibble.grouped_df dplyr## ── Attaching packages ──────────────────────────────────────────── fpp3 1.0.1 ──## ✔ tibble 3.2.1 ✔ tsibble 1.1.6
## ✔ dplyr 1.1.4 ✔ tsibbledata 0.4.1
## ✔ tidyr 1.3.1 ✔ feasts 0.4.1
## ✔ lubridate 1.9.3 ✔ fable 0.4.1
## ✔ ggplot2 3.5.1## ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ──
## ✖ lubridate::date() masks base::date()
## ✖ dplyr::filter() masks stats::filter()
## ✖ tsibble::intersect() masks base::intersect()
## ✖ tsibble::interval() masks lubridate::interval()
## ✖ dplyr::lag() masks stats::lag()
## ✖ tsibble::setdiff() masks base::setdiff()
## ✖ tsibble::union() masks base::union()mydata <- tsibble(
Year = 2015:2019,
Observation = c(123, 39, 78, 52, 110),
index = Year
) %>%
as_tibble(index. = year)
mydata## # A tibble: 5 × 2
## Year Observation
## <int> <dbl>
## 1 2015 123
## 2 2016 39
## 3 2017 78
## 4 2018 52
## 5 2019 110z <- tibble(
Month = c("2019 Jan", "2019 Feb", "2019 Mar", "2019 Apr", "2019 May"),
Observation = c(50, 23, 34, 30, 25)
)Can turn charactehr into month vaiable with yearmonth
z |>
mutate(Month = yearmonth(Month)) |>
as_tsibble(index = Month)## # A tsibble: 5 x 2 [1M]
## Month Observation
## <mth> <dbl>
## 1 2019 Jan 50
## 2 2019 Feb 23
## 3 2019 Mar 34
## 4 2019 Apr 30
## 5 2019 May 25z## # A tibble: 5 × 2
## Month Observation
## <chr> <dbl>
## 1 2019 Jan 50
## 2 2019 Feb 23
## 3 2019 Mar 34
## 4 2019 Apr 30
## 5 2019 May 25library(tsibble)
PBS## # A tsibble: 67,596 x 9 [1M]
## # Key: Concession, Type, ATC1, ATC2 [336]
## Month Concession Type ATC1 ATC1_desc ATC2 ATC2_desc Scripts Cost
## <mth> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
## 1 1991 Jul Concessional Co-payme… A Alimenta… A01 STOMATOL… 18228 67877
## 2 1991 Aug Concessional Co-payme… A Alimenta… A01 STOMATOL… 15327 57011
## 3 1991 Sep Concessional Co-payme… A Alimenta… A01 STOMATOL… 14775 55020
## 4 1991 Oct Concessional Co-payme… A Alimenta… A01 STOMATOL… 15380 57222
## 5 1991 Nov Concessional Co-payme… A Alimenta… A01 STOMATOL… 14371 52120
## 6 1991 Dec Concessional Co-payme… A Alimenta… A01 STOMATOL… 15028 54299
## 7 1992 Jan Concessional Co-payme… A Alimenta… A01 STOMATOL… 11040 39753
## 8 1992 Feb Concessional Co-payme… A Alimenta… A01 STOMATOL… 15165 54405
## 9 1992 Mar Concessional Co-payme… A Alimenta… A01 STOMATOL… 16898 61108
## 10 1992 Apr Concessional Co-payme… A Alimenta… A01 STOMATOL… 18141 65356
## # ℹ 67,586 more rowsPBS |>
filter(ATC2 == "A10")## # A tsibble: 816 x 9 [1M]
## # Key: Concession, Type, ATC1, ATC2 [4]
## Month Concession Type ATC1 ATC1_desc ATC2 ATC2_desc Scripts Cost
## <mth> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
## 1 1991 Jul Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 89733 2.09e6
## 2 1991 Aug Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 77101 1.80e6
## 3 1991 Sep Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 76255 1.78e6
## 4 1991 Oct Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 78681 1.85e6
## 5 1991 Nov Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 70554 1.69e6
## 6 1991 Dec Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 75814 1.84e6
## 7 1992 Jan Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 64186 1.56e6
## 8 1992 Feb Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 75899 1.73e6
## 9 1992 Mar Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 89445 2.05e6
## 10 1992 Apr Concessional Co-paym… A Alimenta… A10 ANTIDIAB… 97315 2.23e6
## # ℹ 806 more rowsPBS |>
filter(ATC2 == "A10") |>
select(Month, Concession, Type, Cost)## # A tsibble: 816 x 4 [1M]
## # Key: Concession, Type [4]
## Month Concession Type Cost
## <mth> <chr> <chr> <dbl>
## 1 1991 Jul Concessional Co-payments 2092878
## 2 1991 Aug Concessional Co-payments 1795733
## 3 1991 Sep Concessional Co-payments 1777231
## 4 1991 Oct Concessional Co-payments 1848507
## 5 1991 Nov Concessional Co-payments 1686458
## 6 1991 Dec Concessional Co-payments 1843079
## 7 1992 Jan Concessional Co-payments 1564702
## 8 1992 Feb Concessional Co-payments 1732508
## 9 1992 Mar Concessional Co-payments 2046102
## 10 1992 Apr Concessional Co-payments 2225977
## # ℹ 806 more rowsPBS |>
filter(ATC2 == "A10") |>
select(Month, Concession, Type, Cost) |>
summarise(TotalC = sum(Cost))## # A tsibble: 204 x 2 [1M]
## Month TotalC
## <mth> <dbl>
## 1 1991 Jul 3526591
## 2 1991 Aug 3180891
## 3 1991 Sep 3252221
## 4 1991 Oct 3611003
## 5 1991 Nov 3565869
## 6 1991 Dec 4306371
## 7 1992 Jan 5088335
## 8 1992 Feb 2814520
## 9 1992 Mar 2985811
## 10 1992 Apr 3204780
## # ℹ 194 more rowsPBS |>
filter(ATC2 == "A10") |>
select(Month, Concession, Type, Cost) |>
summarise(TotalC = sum(Cost)) |>
mutate(Cost = TotalC/1e6)## # A tsibble: 204 x 3 [1M]
## Month TotalC Cost
## <mth> <dbl> <dbl>
## 1 1991 Jul 3526591 3.53
## 2 1991 Aug 3180891 3.18
## 3 1991 Sep 3252221 3.25
## 4 1991 Oct 3611003 3.61
## 5 1991 Nov 3565869 3.57
## 6 1991 Dec 4306371 4.31
## 7 1992 Jan 5088335 5.09
## 8 1992 Feb 2814520 2.81
## 9 1992 Mar 2985811 2.99
## 10 1992 Apr 3204780 3.20
## # ℹ 194 more rowsPBS## # A tsibble: 67,596 x 9 [1M]
## # Key: Concession, Type, ATC1, ATC2 [336]
## Month Concession Type ATC1 ATC1_desc ATC2 ATC2_desc Scripts Cost
## <mth> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
## 1 1991 Jul Concessional Co-payme… A Alimenta… A01 STOMATOL… 18228 67877
## 2 1991 Aug Concessional Co-payme… A Alimenta… A01 STOMATOL… 15327 57011
## 3 1991 Sep Concessional Co-payme… A Alimenta… A01 STOMATOL… 14775 55020
## 4 1991 Oct Concessional Co-payme… A Alimenta… A01 STOMATOL… 15380 57222
## 5 1991 Nov Concessional Co-payme… A Alimenta… A01 STOMATOL… 14371 52120
## 6 1991 Dec Concessional Co-payme… A Alimenta… A01 STOMATOL… 15028 54299
## 7 1992 Jan Concessional Co-payme… A Alimenta… A01 STOMATOL… 11040 39753
## 8 1992 Feb Concessional Co-payme… A Alimenta… A01 STOMATOL… 15165 54405
## 9 1992 Mar Concessional Co-payme… A Alimenta… A01 STOMATOL… 16898 61108
## 10 1992 Apr Concessional Co-payme… A Alimenta… A01 STOMATOL… 18141 65356
## # ℹ 67,586 more rowslibrary(tsibble)
ansett## # A tsibble: 7,407 x 4 [1W]
## # Key: Airports, Class [30]
## Week Airports Class Passengers
## <week> <chr> <chr> <dbl>
## 1 1989 W28 ADL-PER Business 193
## 2 1989 W29 ADL-PER Business 254
## 3 1989 W30 ADL-PER Business 185
## 4 1989 W31 ADL-PER Business 254
## 5 1989 W32 ADL-PER Business 191
## 6 1989 W33 ADL-PER Business 136
## 7 1989 W34 ADL-PER Business 0
## 8 1989 W35 ADL-PER Business 0
## 9 1989 W36 ADL-PER Business 0
## 10 1989 W37 ADL-PER Business 0
## # ℹ 7,397 more rowsautopilot will take first variable if you are not speicific, you can add geompoint to the time series to make it look nice.
melsyd_economy <- ansett |>
filter(Airports == "MEL-SYD", Class == "Economy") |>
mutate(Passengers = Passengers/1000)
autoplot(melsyd_economy, Passengers) +
labs(title = "Ansett airlines economy class",
subtitle = "Melbourne-Sydney",
y = "Passengers ('000)")
set.seed(30)
y <- tsibble(sample = 1:50, wn = rnorm(50), index = sample)
y |> autoplot(wn) + labs(title = "White noise", y = "")