(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
Kaiser asks:
Trying to figure out what are some keywords to research for this problem I’m trying to solve. I need to estimate seasonality but without historical data. What I have are multiple time series of correlated metrics (think department store sales, movie receipts,
etc.) but all of them for 52 weeks only. I’m thinking that if these metrics are all subject to some underlying seasonality, I should be able to estimate that without needing prior years data.
My reply:
Can I blog this and see if the hive mind responds? I’m not an expert on this one.
My first thought is to fit an additive model including date effects, with some sort of spline on the date effects along with day-of-week effects, idiosyncratic date effects (July 4th, Christmas, etc.), and possible interactions.
Actually, I’d love to fit something like that in Stan, just to see how it turns out. It could be a tangled mess but it could end up working really well!
Please comment on the article here: Statistical Modeling, Causal Inference, and Social Science
