README.md

In mervynakash/ninjArimaR: Returns the optimal AR order, degree of difference and MA order for Arima Model for Time Series Analysis.

Why use ninjArimaR?

The idea of this package is pretty simple. Input the time series variable in the ninjArima() method and in return this package will help you get the optimal AR order, degree of differencing and MA order. Now just use this returned value in an arima(ts, order = <return>) model and predict your time series.

This package is exculsively for R Programmers who have trouble understanding the ARIMA model and if the time series data set is quite huge then the auto.arima() method of the library(forecast) will take a huge amount of time to execute.

Installation

To get the current development version from github:

install.packages("devtools")
devtools::install_github("mervynakash/ninjArimaR")

Functions:

ninjArima(<ts>) : The method takes a time series data as an input and returns you the optimal order to put in ARIMA model. Let's take a look in an example.

kings <- scan("http://robjhyndman.com/tsdldata/misc/kings.dat",skip=3)
kingsSeries <- ts(kings)
order <- ninjArima(kingsSeries)

model <- arima(kingsSeries, order = order)
pred_arima <- predict(model, n.ahead = 10)
print(pred_arima)

Conclusion

There will be a lot of bugs and errors and I would be highly honored if you developers would mail me at [e-mail]. Any type of feedback and criticism is appreciated and hope to improve my algorithm for the benefits of R community.

Thank You. Happy Coding!!!!

mervynakash/ninjArimaR documentation built on May 4, 2019, 3:09 a.m.