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I am new to time series analysis and wanted to know what the best r package is to solve my dilema. I have a data frame with the following columns: 

      Date    Spend   Result
2017-06-22        2       17
2017-06-21        5       19
2017-06-20       11       45
2017-06-19       34       78
2017-06-18       23       56
2017-06-17       12       34

The business problem trying to be solved is that based on the seasonality of the data and the amount spent, can I predict the Result column.

For example, let's say I wanted to increase my spend to $45 more per day, can I predict the Result based on the spend and the time of year?

I was going to use a generalized additive model but that only takes 1 variable into account. Is it possible to do a simple regression analysis with this with time being one of the variables?

I was thinking of taking the month from the date column and making the month dummy variables. Not sure if there is a better way though.

Thanks!

nak5120
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  • Better if you ask on [Cross Validate](https://stats.stackexchange.com/) – M-- Jun 22 '17 at 22:02
  • Just posted it, thanks. Can be found here: https://stats.stackexchange.com/questions/286836/time-series-analysis-model-choosing – nak5120 Jun 22 '17 at 22:05

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