I have some data that varies over time, and cannot be described by a simple model. In fact we don't care what the model is at all, we just want to know whether it is significantly non-zero at any point in time. Ideally, the result would also tell us at which time points the data is significantly different from 0.
It is possible to do bootstrapping, but I am wondering if there is a more specific way to assess significance (a specific type of ANOVA, or t-test with corrections for multiple comparisons - but how to determine number of comparisons since the data is clearly correlated in time.).
Thanks in advance - I'm sure this is a common problem, but after hours of reading I still can't find a clear answer.