Time Series Analysis in R
Time Series in R is used to see how an object behaves over a period of time. In R, it can be easily done by ts() function with some parameters. Time series takes the data vector and each data is connected with timestamp value as given by the user. This function is mostly used to learn and forecast the behavior of an asset in business for a period of time. For example, sales analysis of a company, inventory analysis, price analysis of a particular stock or market, population analysis, etc.
Syntax: objectName <- ts(data, start, end, frequency)
- data represents the data vector
- start represents the first observation in time series
- end represents the last observation in time series
- frequency represents number of observations per unit time. For example, frequency=1 for monthly data.
Note: To know about more optional parameters, use the following command in R console:
Example: Let’s take the example of COVID-19 pandemic situation. Taking a total number of positive cases of COVID-19 cases weekly from 22 January 2020 to 15 April 2020 of the world in data vector.
Multivariate Time Series
Multivariate Time Series is creating multiple time series in a single chart.
Example: Taking data of total positive cases and total deaths from COVID-19 weekly from 22 January 2020 to 15 April 2020 in data vector.
Forecasting can be done on time series using some models present in R. In this example, Arima automated model is used. To know about more parameters of arima() function, use the below command.
In the below code, forecasting is done using forecast library and so, installation of forecast library is necessary.
After executing the above code, the following forecasted results are produced.
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95 2020.307 2547989 2491957 2604020 2462296 2633682 2020.326 2915130 2721277 3108983 2618657 3211603 2020.345 3202354 2783402 3621307 2561622 3843087 2020.364 3462692 2748533 4176851 2370480 4554904 2020.383 3745054 2692884 4797225 2135898 5354210
Below graph plots estimated forecasted values of COVID-19 if it continues to be widespread for the next 5 weeks.