# @RISK Vs R. Monte Carlo simulation in R?

Are there any cheaper or open source alternatives to @RISK or are there packages for R that would be able to perform the same tasks?

@RISK (pronounced “at risk”) performs risk analysisusing Monte Carlo simulation to show you many possible outcomes in your spreadsheet model—and tells you how likely they are to occur. It mathematically and objectively computes and tracks many different possible future scenarios, then tells you the probabilities and risks associated with each different one. This means you can judge which risks to take and which ones to avoid, allowing for the best decision making under uncertainty. (Taken from their website)

My main purposes for it would be for the construction company I currently work for:

 Able to provide more accurate models for job costing, e.g. time to construct certain parts, associated costs, etc.

Provide more accurate models in regard to advertising and marketing, allowing us to better understand and predict what provides the better return.


If this isn't the right forum for this question, please tell me where it needs to be asked.

Thank you,

• You could give a link to "@RISK" and outline what it does, what you've looked for already, which packages you have already excluded from doing the thing you want to do, or outline the thing you want to do. – Spacedman May 9 '16 at 17:23
• I've updated my question, thank you for your post. Also, I'm open to any software, I've yet to exclude anything. I would just like to be able to perform these tasks more cost effectively. – user18557 May 9 '16 at 17:45
• If you want to have more products recommended, you could try softwarerecs.stackexchange.com or for more theoretical answers: quant.stackexchange.com – knb Jul 17 '17 at 7:45