Time series analysis using techniques in R

https://rpubs.com/Deeandrea/276948

RPubs - Basic Time Series Analysis

https://2stndard.tistory.com/126

시계열 이상치 탐색 in R

 

https://rpubs.com/AlgoritmaAcademy/multiseasonality

RPubs - Forecasting Time Series with Multiple Seasonal

ts객체 만들때 frequency를 어떻게 설정하는지

After you have read the time series data into R, the next step is to store the data in a time series object in R, so that you can use R many functions for analysing time series data. To store the data in a time series object, we can use the ts() function in R. Sometimes the time series data set that you have may have been collected at regular intervals that were less than one year, for example, monthly or quarterly. In this case, you can specify the number of times that data was collected per hour by using the frequency parameter in the ts() function. Because our each row representing a data within hourly interval, you can set frequency=24, and we will only used AEP provider.

 

5년간 측정된 데이터가 있다고 할때 

->  데이터가 월별로 관측되면 

1월 : value , 2월 : value , 3월 : value ,..., 12월 : value이므로 frequency = 12

이때 data 행 수는 12(1년에 12개월) * 5

-> 데이터가 주별로 관측되면

1주 : value, 2주 : value,..., 51주 ; value 이므로 frequency = 51

이때 data 행 수는 51(1년에 51주) * 5

-> 데이터가 일별로 관측되면

1일 : value, 2일 : value ,..., 365일 : value이므로 frequency = 365

이때 data 행 수는 365(1년에 365일) * 5

-> 데이터가 시간별로 관측되면

00시 : value, 01시 : value,..., 23시 : value이므로 frequency = 24

이때 data 행 수는 24*365(1년에 24시간이 365번) * 5

 

 

https://todayisbetterthanyesterday.tistory.com/37

[ADP] R로 하는 시계열 분석 실습(분해시계열, ARIMA)

 

 

 

https://otexts.com/fpp3/seasonal-arima.html

9.9 Seasonal ARIMA models | Forecasting: Principles and Practice (3rd ed)

 

pdq, PDQ정하는법

https://www.youtube.com/watch?v=lzKP70lsc5s