I've been working with PyMC for a bit, and am stuck on this one. I see example on fitting time series, in the tutorial and others like:
http://lighthouseinthesky.blogspot.com/2011/10/curve-fitting-part-5-pymc.html
and
However, in each case, we either have a single variable, or data for two or more variables for the same time points (so the vectors are all of the same length). What happens if my data is like:
t=[1,2,3] x=[.5,.8,.2] and
t=[1.5,2.5] y=[.1,.5] with some simple model, like
x=a*t+b y=c*t+d the model isn't important. the point is that the "observed" data have different time points. I haven't been able to find any example like this, without perfectly aligned data. Are there any? Is there a simple example that someone could point out?
thanks!
Brian Blais Best Answer
Brian,
I may be misunderstanding what you are after, but if you are modeling time t explicitly, it should not matter that they are not aligned, does it? You might have a peek in Chapter 11 of Gelman and Hill for examples of Bayesian models for longitudinal data.
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