I’d like to declare multiple Gaussian random walks which evolve independently. Following an earlier post asking about multiple drifts (Can I instantiate multiple random walks with different drifts), I tried:
mean_sigma = pm.HalfNormal('mean_rw_sigma', 1., shape=n_tourneys) prior_means = pm.GaussianRandomWalk('prior_means', sigma=mean_sigma, shape=(n_years-1, n_tourneys))
However, this doesn’t compile:
ValueError: Input dimension mis-match. (input.shape = 3, input.shape = 4)
I thought I could maybe do the MvGaussianRandomWalk with a diagonal covariance, but I’ve been unable to create a diagonal covariance matrix, so I’d be grateful for any pointers. Apologies if I’m doing something silly, I’m pretty new to pymc3!