R Time series Results analysis always remains the same.

Question

I'm trying to do time series analysis in R. I have time series data like this.

    Month       Year    Value 
    December    2013    5300
    January     2014    289329.8
    February    2014    596518
    March       2014    328457
    April       2014    459600
    May         2014    391356
    June        2014    406288
    July        2014    644339
    August      2014    251238
    September   2014    386466.5
    October     2014    459792
    November    2014    641724
    December    2014    399831
    January     2015    210759
    February    2015    121690
    March       2015    280070
    April       2015    41336

Googling I found that I can use the auto.arima function to predict the result. I was able to write R code for forecasting using the auto.arima function

    data <- c(5300,289329.8,596518,328457,459600,391356,406288,644339,251238,386466.5,459792,641724,399831,210759,121690,280070,41336)
    data.ts <- ts(data, start=c(2013, 12), end=c(2015, 4), frequency=12) 
    plot(data.ts)
    fit <- auto.arima(data.ts)
    forec <- forecast(fit)
    plot(forec)

The problem is that my forecast always remains the same.

Can someone tell me what is going wrong. or help me fix my forecast. Thanks

Answer 1

There is nothing bad. This is just your automatic prediction: a model containing only interception (medium).

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