- RAIN CITY TIME MACHINE CODE
- RAIN CITY TIME MACHINE SERIES
RAIN CITY TIME MACHINE SERIES
Create a time series object of the precipitation data for the year starting from 1815 and plot that time-series.Read the data containing records of annual precepitation (in inches) in London (data is available here).
NYC_ts_adjusted <- NYC_ts_data - NYC_ts_comp$seasonal
The seasonal time series data of NYC can be seasonally adjusted by subtracting its seasonal component from the original time series. Plot all the components of the NYC time series in a single plot. Now, we can separate obtain each of the three components of the decomposed NYC data. For seasonal data such as that of births in NYC, the decomposition can be carried out using the decompose() function since it also has a seasonal component apart from the trend and irregular ones. It can be observed that incrementing the order of SMA smoothens the plot more i.e. reduces fluctuations in the trend. Similarly, we can change the order to say 8 and observe the change in the trend. (‘n’ parameter here specifies the order of SMA) We first smoothen the kings’ time series data using SMA() function of the TTR package (where SMA stands for ‘ simple moving average’) for getting the trend component. A seasonal data additionally has a seasonal component. A trend component and an irregular component. Time series decomposition is a process of decomposing the time series data into components viz. Plot the time-series version of all the three datasets (kings’ data, NYC’s data and souvenir shop’s data). Convert the souvenir shop’s data into a time series object. Read the data containing monthly records of a souvenir shop in Australia. Also, we specify start=c(1950,1)) as a parameter to ts() indicating that the data should start from the year 1950 and there should 1 sample per year for each month. ‘frequency’ parameter of the ts() function should be set to 12 for month-wise data. Store NYC’s data into an R time series object. Similarly, read the New York City (NYC)’s data containing a monthly record of a number of births in the city. 
Store the kings’ data into a time series object for performing time series analysis.Read the data containing age of various kings when they died.Output: package ‘rmeta’ successfully unpacked and MD5 sums checkedĬ:\Users\Lenovo\AppData\Local\Temp\RtmpUJ2vKU\downloaded_packages
RAIN CITY TIME MACHINE CODE
Step-wise explanation of the code is as follows: Time-Series AnalysisĬheck if the package has been installed by displaying the whole list of packages The code here has been implemented using RStudio IDE (version ).
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