I have a model that attempts to estimate parameters of a curve that has a linear component followed by an exponential curve. That is, for time-t < t_2 the curve is linear, and for t \geq t_2 the curve is exponential. The conditional equation for the curve is \begin{align} H(t_n) = \begin{cases} \f…

That sounds like a promising suggestion but i don’t think i am quite there yet - still getting a similar error. Possibly my implementation is off? See below: import numpy as npy import pymc3 as pm from theano import tensor as tt from theano import shared, scan from theano.ifelse import ifelse Hd =…

I guess i don’t need scan for this task: import numpy as npy import pymc3 as pm from theano import tensor as tt Hd = npy.array([629.52234607, 18969.57367046, 238960.91467992, 328497.85275376]) rows = npy.array([2, 9, 37, 81]) tend = 21 dt = 0.25 tSeq = npy.arange(0, tend+dt, dt) def logistic(L, x…

It seems the disparity between my parameters B and H_{ult} was the second issue. For my synthetic data, I had B=1.127e-2 and H_{ult}=3.38e+5. If I change the units for H_{ult} to reduce the magnitude by three orders, I no longer get the “mass matrix contains zero on diagonal” error and the sampling …

Model with conditional parameters causing mass matrix to contain zeros on diagonal

Questions

junpenglao January 1, 2020, 11:47pm 2

You can try a break point model (ideally with smooth switch point), for example see: Switch point Metropolis tuning

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Model with conditional parameters causing mass matrix to contain zeros on diagonal

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