Hi Ryan,
I can't speak to accounting in particular, but I do know there are a number of packages focused on time series analysis and forecasting. And in general, R is a great choice for custom reporting and modeling. The CRAN Task View on time series analysis may be a good place to start:
Base R ships with a lot of functionality useful for time series, in particular in the stats package. This is complemented by many packages on CRAN, which are briefly summarized below. There is overlap between the tools for time series and those...
There have also been some recent threads here which might be relevant to the modeling questions:
Every time I need to do a time-series forecasting, I use the tool that I know well: the forecast package and functions from there (most commonly ets).
The problem is that I find it to be a pain in the ass to work with ts and xts objects and go out of my way to construct a model.
There is gotta be a better way!
How do you do time-series forecasting? What are your best practices?
Hey Everyone,
Long time follower/learner of the #rstats hashtag and various other places where R folks congregate online to help each other. disclaimer: I've never posted in any forum, so feel free to let me know if this is the wrong avenue for getting some help, but I'm having a problem that I can't solve despite several attempts to find a clear explanation.
Description of Data: I have a two very large data sets related to school finance and school districts. One contains 25 years worth of Actual School Finance data for every school district in Texas, comes from the Texas Education Agency, and has over 100 variables. The other has 50 years of Public Finance Data for every unified school d…
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