Working out the multiple uncertainty computational performance and noise forms. Fixing a few things in the way log-normal noise was calculated. Uniform noise in particular can still give rather non-smooth policy, needs a bit of digging. Uniform noise doesn’t show the non-monotonicity of the log-normal noise in measurement uncertainty though.
- A few small tweaks to probability calculations
- Handle the case of mu = grid zero, not just exactly zero, to avoid introducing NAs
- Calculate dlnorm as
(x_grid/mu, 0, sigma), rather than as
(x_grid, mu, sigma).
- Transpose of measurement error in
M %*% F. Because now we want to treat x as given, integrate over range of y? (no, probably not?)
- standardize noise level between old and g 12:52 pm 2012/11/22
With transposed M time F. (include image) 01:04 pm 2012/11/22
And now without transpose, M %*% F 01:07 pm 2012/11/22
Larger (log-normal in all variables) noise, weirder results. 01:39 pm 2012/11/22
- Changes improving performance of F calculation (rate-limiting step)
- vectorized calculation of mu.
- matrix-based calc of deterministic part of growth rate 02:13 pm 2012/11/22
- Another efficiency change. Not identical but appears to be a decent approximation: Snap mu to the x_grid, and look up the pdfn value rather than calculating it each time in F. 03:00 pm 2012/11/22
Now pretty efficient. Matrix multiplication is dominant time sink, followed by the applys.
snap_to_grid is probably the slowest functional contribution.