해당 자료는 전북대학교 이영미 교수님 2023고급시계열분석 자료임

TS기본

예시1

x <- 1:10

class(x)

'integer'

x <- ts(1:10)

class(x)

'ts'

x <- ts(rnorm(50), start=c(2000,1), frequency=12)

start=c(2000,1) 은 2000년도 1월부터 시작, frequency=12로 설정하면 월별 데이터
frequency=4로 하면 분기별로
frequency=52로 하면 주별로
frequency=1로 하면 1년

A Time Series: 5 × 12
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2000	0.76405413	-1.02349881	-0.51959564	0.01864085	-0.60774019	0.14672756	1.29754383	-0.48970178	0.63146949	0.95926188	-0.25685314	-1.29338383
2001	-1.59141361	0.40743501	1.75707309	-0.99527927	-1.14542320	-0.37712164	1.17125683	-1.77853599	0.88462388	0.38648820	0.63353985	0.14774167
2002	-1.27983177	0.40469783	-0.79593176	-0.92399600	0.47708488	0.23482996	-1.47308579	0.52336346	1.52855291	-0.22313437	0.28595267	-1.98182541
2003	0.60718388	-1.21229303	-0.62694271	1.66803342	-0.32590005	-1.07216211	-0.66451496	-0.54215015	-0.73426974	-0.91737960	0.92539709	0.44326098
2004	-0.57459795	0.84987553

cycle(x) #주기

A Time Series: 5 × 12
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2000	1	2	3	4	5	6	7	8	9	10	11	12
2001	1	2	3	4	5	6	7	8	9	10	11	12
2002	1	2	3	4	5	6	7	8	9	10	11	12
2003	1	2	3	4	5	6	7	8	9	10	11	12
2004	1	2

- 주기

분해법 같은 거 할 때 주기가 설명변수로 들어갈 때가 있다.

class(cycle(x))

'ts'

time(x)

A Time Series: 5 × 12
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
2000	2000.000	2000.083	2000.167	2000.250	2000.333	2000.417	2000.500	2000.583	2000.667	2000.750	2000.833	2000.917
2001	2001.000	2001.083	2001.167	2001.250	2001.333	2001.417	2001.500	2001.583	2001.667	2001.750	2001.833	2001.917
2002	2002.000	2002.083	2002.167	2002.250	2002.333	2002.417	2002.500	2002.583	2002.667	2002.750	2002.833	2002.917
2003	2003.000	2003.083	2003.167	2003.250	2003.333	2003.417	2003.500	2003.583	2003.667	2003.750	2003.833	2003.917
2004	2004.000	2004.083

예시2

x <- rnorm(100)

class(x)

'numeric'

t <- 1:100

plot(t,x, type='l')

type=‘l’ 하면 선으로 그려짐

y <- as.ts(x)

class(y)

'ts'

plot(y)

y를 ts로 바꿔준 후 plot그리면 바로 선으로 그려짐

plot.ts(x)

ts.plot(x)

예시3

z <- ts(matrix(rnorm(300), 100, 3), start=c(2000), frequency=12)

A Time Series: 100 × 3
	Series 1	Series 2	Series 3
Jan 2000	1.29698875	-1.21674471	-1.045034994
Feb 2000	0.25714581	-0.46422565	0.483273186
Mar 2000	-1.69609518	0.11543522	1.394646640
Apr 2000	-0.02172058	0.43036387	0.905497648
May 2000	-0.39205715	-0.27943394	1.358016569
Jun 2000	0.50886335	0.85316956	-1.895619864
Jul 2000	-1.80530553	1.71537527	1.329138264
Aug 2000	-1.46328716	-0.31392842	0.742000641
Sep 2000	-1.38169601	-1.26421866	-0.191226610
Oct 2000	-0.01805485	0.93875696	2.068855082
Nov 2000	-0.34166996	-1.61838098	0.639833161
Dec 2000	2.18777732	0.62720494	1.453509388
Jan 2001	-0.48260923	-0.28668534	1.773957684
Feb 2001	-0.16098004	-1.01794429	-0.183156085
Mar 2001	0.59254034	2.47052543	-0.809340939
Apr 2001	-0.58943389	0.82159951	0.352739904
May 2001	-1.45154532	-0.43198993	0.665977309
Jun 2001	0.46219480	0.19420399	-0.262522937
Jul 2001	0.74171572	0.88243415	0.892556497
Aug 2001	-0.53807879	-0.58672603	0.545136112
Sep 2001	0.65559328	0.91101814	-2.056745676
Oct 2001	0.36380952	0.26730273	0.553534241
Nov 2001	0.49678797	0.72762693	1.365226501
Dec 2001	1.14095522	-1.30247190	1.510088305
Jan 2002	-1.39845866	1.80914173	0.247411534
Feb 2002	0.54354719	0.40637855	2.951693379
Mar 2002	0.74456311	-0.97149128	-0.424397231
Apr 2002	0.67847157	-1.33946923	-1.009035652
May 2002	-0.71580510	-1.03397342	0.740221981
Jun 2002	-0.41755001	-0.10206794	1.570414318
Jul 2002	0.17680380	0.43245983	1.625357479
Aug 2002	-0.95681583	-0.32390645	-0.709353518
Sep 2002	0.78065065	2.76478866	-0.127425483
Oct 2002	1.02147488	0.26340296	-1.306210735
Nov 2002	-0.61802357	0.73282875	-0.779533677
Dec 2002	-0.98624272	-0.90351530	0.559447943
Jan 2003	-1.67644507	-0.96854559	0.352028417
Feb 2003	-0.02038246	-1.14873244	0.313497750
Mar 2003	-0.26066156	-0.33632808	0.456722618
Apr 2003	1.67542156	1.21970305	0.230345692
May 2003	0.26359387	0.71395285	1.116902239
Jun 2003	1.45528996	1.10804737	0.542625091
Jul 2003	-0.71892538	0.35460415	0.863238040
Aug 2003	-1.31576484	-0.49592678	1.783651647
Sep 2003	-0.20677657	0.94086539	0.108162065
Oct 2003	-0.41455675	-0.63930979	-0.520634930
Nov 2003	-0.53695148	-1.29420682	1.743452058
Dec 2003	0.85407196	-0.45433578	-0.090949969
Jan 2004	0.49875472	0.74599358	0.114811798
Feb 2004	-0.21734313	-1.55225754	-0.295416275
Mar 2004	-0.16518469	0.63871891	-0.307326165
Apr 2004	1.34706900	-0.81975832	0.841763649
May 2004	1.46561716	0.05836098	1.370650302
Jun 2004	0.91005600	1.48060158	-0.924395745
Jul 2004	1.75993687	0.53251578	0.007020867
Aug 2004	-1.33355445	-0.66142666	-0.956165251
Sep 2004	-2.32004900	0.49294086	0.438495174
Oct 2004	-1.28912660	0.37384792	-0.721941570
Nov 2004	-0.89574330	-1.18158398	-0.308383156
Dec 2004	-2.16302760	0.61114109	-0.159999432
Jan 2005	0.06904502	0.45510869	0.542888786
Feb 2005	-1.76391821	-0.37935623	0.674218646
Mar 2005	2.27249463	-1.01247888	-0.794283698
Apr 2005	0.20353326	-2.09981742	-2.445789016
May 2005	-0.34161710	-0.11308729	1.194669309
Jun 2005	-0.47317357	-0.96164561	-1.105428534
Jul 2005	0.88899272	-0.46110042	1.018510347
Aug 2005	-1.21056402	0.94189524	-0.154002748
Sep 2005	1.27189344	-0.09086265	0.853223269
Oct 2005	2.43673610	-0.38708700	-0.114912446
Nov 2005	-0.70430531	0.29337553	-0.231400148
Dec 2005	0.21192641	1.08547553	1.758685933
Jan 2006	-0.36607787	-0.21454928	0.604770490
Feb 2006	2.74487541	0.37143248	-1.804909791
Mar 2006	-0.06660497	-0.49540231	0.520447152
Apr 2006	-0.36036564	-0.65447797	1.101548824
May 2006	0.03937687	0.29065032	0.710582404
Jun 2006	1.20196082	-2.38804583	-0.661208046
Jul 2006	2.42037478	0.92585911	-0.164038692
Aug 2006	-0.81440983	-1.34864791	-0.349078183
Sep 2006	0.55318248	-0.76005851	0.442683600
Oct 2006	-1.66074158	0.09216394	-1.290911876
Nov 2006	-1.53176534	-0.28728584	-1.336682588
Dec 2006	-0.21676828	-0.10978893	-0.898920033
Jan 2007	-0.05676096	0.88120659	-1.211459957
Feb 2007	1.60050550	1.10863397	0.801239884
Mar 2007	1.18151898	1.22710760	0.234467028
Apr 2007	1.86273043	0.64789357	0.968746102
May 2007	-0.19704726	-0.31664389	0.115593106
Jun 2007	-0.80236520	-0.46278229	-0.798281008
Jul 2007	-0.57023657	-0.28156889	1.988958919
Aug 2007	0.39209971	-2.77298749	1.456734626
Sep 2007	-2.58484490	1.01233158	0.106086064
Oct 2007	1.57908149	-0.75397813	-0.442861061
Nov 2007	0.08697194	-1.82803417	-1.439861978
Dec 2007	-0.26444040	0.56057798	0.428862529
Jan 2008	0.65498531	-2.29645430	-0.144352451
Feb 2008	2.18246630	0.00740514	0.010789788
Mar 2008	-0.79253588	-0.35783010	-1.029779770
Apr 2008	1.31979636	0.09844285	-0.198100075

plot(z)

plot.ts(z)

plot.ts(z, plot.type="single", col=1:3, lty=1:3)

ts.plot(z, col=1:3)

예시4: iris 데이터

head(iris)

A data.frame: 6 × 5
	Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
	<dbl>	<dbl>	<dbl>	<dbl>	<fct>
1	5.1	3.5	1.4	0.2	setosa
2	4.9	3.0	1.4	0.2	setosa
3	4.7	3.2	1.3	0.2	setosa
4	4.6	3.1	1.5	0.2	setosa
5	5.0	3.6	1.4	0.2	setosa
6	5.4	3.9	1.7	0.4	setosa

t.iris <- as.ts(iris[,-5])

마지막 자료는 범주형 자료라서 빼줌

class(t.iris)

'mts'
'ts'
'matrix'

mts: multiple time series

t.iris[10,3]

Petal.Length: 1.5

matrix에 사용하는 모든 함수 같은걸 사용할 수 있다.

head(t.iris)

A matrix: 6 × 4 of type dbl
Sepal.Length	Sepal.Width	Petal.Length	Petal.Width
5.1	3.5	1.4	0.2
4.9	3.0	1.4	0.2
4.7	3.2	1.3	0.2
4.6	3.1	1.5	0.2
5.0	3.6	1.4	0.2
5.4	3.9	1.7	0.4

plot.ts(t.iris)

ts.plot(t.iris, col=1:4)

Date

\(r_{t,3M} = \frac{y_{t+3M}}{y_t}-1\)

3개월 후의 수익률을 구한다 =

Sys.Date()

2023-09-17

현재 날짜 불러옴

date()

'Sun Sep 17 16:26:57 2023'

현재 날짜와 시간

a <- Sys.Date()

class(a)

'Date'

a <- "2023-09-17"
a

'2023-09-17'

class(a)

'character'

a_date <- as.Date(a)

a_date

2023-09-17

따옴표가 사라짐!

class(a_date)

'Date'

a <- as.Date(c("2023-09-17","2024-01-01"))
a

2023-09-17
2024-01-01

a[2] - a[1]

Time difference of 106 days

a_chr <- as.character(a)

a_chr

'2023-09-17'
'2024-01-01'

a_chr[2] - a_chr[1]

ERROR: Error in a_chr[2] - a_chr[1]: non-numeric argument to binary operator

문자라 안됨

a[1] + 7

2023-09-24

a[1] - 7

2023-09-10

a[1]

2023-09-17

format(a[1], format="%B-%d-%y")

'9월-17-23'

as.Date("2023-09-17")

2023-09-17

b <- as.Date("09/17/23", format="%m/%d/%y")

as.Date("09/17/23") 로 하면 09년으로 파악할 수도 있으므로 위에처럼 format형식을 지정해주는 것이 좋다.

2023-09-17

weekdays(b)

'일요일'

# ?Date

# ?format

# ?as.Date

Lubridate package 활용하기

install.packages("lubridate")

Installing package into ‘/home/coco/R/x86_64-pc-linux-gnu-library/4.2’
(as ‘lib’ is unspecified)

Warning message in install.packages("lubridate"):
“installation of package ‘lubridate’ had non-zero exit status”

library(lubridate)


Attaching package: ‘lubridate’


The following objects are masked from ‘package:base’:

    date, intersect, setdiff, union

날짜, 시간 정보를 추출

a <- today()

2023-09-17

class(a)

'Date'

year(a)

2023

month(a)

day(a)

wday(a)

기본세팅 1:일요일, 2: 월요일 …

wday(a, label=TRUE)

일

Levels:

'일'
'월'
'화'
'수'
'목'
'금'
'토'

class(wday(a,label=TRUE))

'ordered'
'factor'

now()

[1] "2023-09-17 16:41:22 KST"

class(now())

'POSIXct'
'POSIXt'

now <- now()

hour(now)

minute(now)

second(now)

29.3091588020325

ymd("2023-09-17")

2023-09-17

ymd: year month day

mdy("09-17-23")

2023-09-17

ymd(20230917)

2023-09-17

ymd("2023 Sep 17") # locale="USA")

2023-09-17

뒤에 locale 하면 안되넹

ymd("2023/09/17")

2023-09-17

a <- ymd_hms("2023-09-17 09:00:00", tz="Asia/Seoul")

hms: 시간

 ymd_hms("2023-09-17 09:00:00")

[1] "2023-09-17 09:00:00 UTC"

ymd_hms("2023-09-17 09:00:00", tz="Asia/Seoul")

[1] "2023-09-17 09:00:00 KST"

[1] "2023-09-17 09:00:00 KST"

with_tz(a, tz="America/New_York")

[1] "2023-09-16 20:00:00 EDT"

tz: time zone
한국은 현재 9.17. 인데 미국은 9. 16.일수도 있음. 미국을 9. 17.로 바꾸어버리면 한국 기준으로 미국의 데이터는 미래 데이터인 경우가 있다! 그러므로 time zone을 생각해야함!!ㅡ
설명변수에 미래변수가 있으면 안된다.

ym(202309)

2023-09-01

hms("11:30:00")

11H 30M 0S

hm("11:30")

11H 30M 0S

now <- now()

now

[1] "2023-09-17 16:43:59 KST"

update(now, years=2000)

[1] "2000-09-17 16:43:59 KST"

필요한 날짜만 변경