Package-free solution [PK / PD]
Hi yung-jin,
Yes it can. This time it was a one-domensional problem, but it can be extended to any number of dimensions. It is a typical grid search. The trouble is that for each new dimension the computation time is multiplied by a factor Gridsize. In this case I used 10000 steps as this is just one dimension. But if we try two dimensions and use 10000 steps per dimension, well, it is going to be (10^5)^2 loops then and you might be late for supper. Better to decrease the grid density then iterate more times over the optimiser then. Of course one can work with X steps in one dimension and Y steps in the other dimension if a speed gain is envisaged. Everything is possible.
❝ Very smart numerical approach. Works perfectly. Simple and clean. Can this approach be used to solve more one parameters, such as K10 and K01 simultaneously? Hmm...
Yes it can. This time it was a one-domensional problem, but it can be extended to any number of dimensions. It is a typical grid search. The trouble is that for each new dimension the computation time is multiplied by a factor Gridsize. In this case I used 10000 steps as this is just one dimension. But if we try two dimensions and use 10000 steps per dimension, well, it is going to be (10^5)^2 loops then and you might be late for supper. Better to decrease the grid density then iterate more times over the optimiser then. Of course one can work with X steps in one dimension and Y steps in the other dimension if a speed gain is envisaged. Everything is possible.
—
Pass or fail!
ElMaestro
Pass or fail!
ElMaestro
Complete thread:
- 1 compartment model with lag time jag009 2013-07-17 15:58 [PK / PD]
- solve for k01? Helmut 2013-07-17 16:08
- solve for k01? jag009 2013-07-17 16:19
- solve for k01? ElMaestro 2013-07-17 17:09
- no closed form Helmut 2013-07-17 23:01
- solve for k01? jag009 2013-07-17 16:19
- 1 compartment model with lag time yjlee168 2013-07-17 20:57
- Package-free solution ElMaestro 2013-07-17 21:53
- Package-free solution yjlee168 2013-07-17 22:11
- Package-free solutionElMaestro 2013-07-17 22:27
- Package-free solution yjlee168 2013-07-17 22:42
- Package-free solutionElMaestro 2013-07-17 22:27
- Package-free solution ElMaestro 2013-07-17 23:21
- A new R-King was born d_labes 2013-07-18 08:45
- Brent ElMaestro 2013-07-18 09:07
- A new R-King was born yjlee168 2013-07-18 10:21
- OT: TTT in bear Helmut 2013-07-18 20:28
- OT: TTT in bear yjlee168 2013-07-18 22:17
- OT: TTT subtleties d_labes 2013-07-19 09:47
- OT: TTT subtleties yjlee168 2013-07-20 19:44
- OT: beyond TTT? Helmut 2013-07-21 00:08
- OT: beyond TTT? yjlee168 2013-07-22 13:45
- OT: keep TTT! Helmut 2013-07-22 14:21
- OT: keep TTT! yjlee168 2013-07-22 23:42
- OT: EOD (here) Helmut 2013-07-23 01:06
- OT: keep TTT! yjlee168 2013-07-22 23:42
- OT: keep TTT! Helmut 2013-07-22 14:21
- OT: beyond TTT? yjlee168 2013-07-22 13:45
- OT: beyond TTT? Helmut 2013-07-21 00:08
- OT: TTT subtleties yjlee168 2013-07-20 19:44
- OT: TTT subtleties d_labes 2013-07-19 09:47
- OT: TTT in bear yjlee168 2013-07-18 22:17
- OT: TTT in bear Helmut 2013-07-18 20:28
- Package-free solution yjlee168 2013-07-18 10:27
- Thank you guys! jag009 2013-07-18 16:37
- Thank you guys! ElMaestro 2013-07-18 18:57
- Thank you guys! jag009 2013-07-19 20:40
- Thank you guys! ElMaestro 2013-07-18 18:57
- Thank you guys! jag009 2013-07-18 16:37
- A new R-King was born d_labes 2013-07-18 08:45
- Package-free solution yjlee168 2013-07-17 22:11
- solve for k01? Helmut 2013-07-17 16:08