# Fitting ODE models: best/efficient practices?

**URL:** <https://discourse.mc-stan.org/t/fitting-ode-models-best-efficient-practices/21018>\
**Category:** General\
**Tags:** ode\
**Created:** [February 26, 2021, 7:16pm UTC](https://discourse.mc-stan.org/t/fitting-ode-models-best-efficient-practices/21018 "2021-02-26T19:16:16Z")\
**Posts on this page:** 1\
**Showing post:** 66

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**Author:** ![bbbales2](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/bbbales2/32/77_2.png) [@bbbales2](https://discourse.mc-stan.org/u/bbbales2)\
**Post date:** [March 16, 2021, 12:47pm UTC](https://discourse.mc-stan.org/t/fitting-ode-models-best-efficient-practices/21018/66 "2021-03-16T12:47:59Z")

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> [@Funko\_Unko](#):
>
> That’s the window for the step size adaptation before we start to sample

Oooh, makes sense.

All through warmup the stepsize is being adapted, so I’d expect the refined timestep would be unnecessary if more warmup was the follow.

It’s surprising that it worked worse in this case.

There’s a few interesting posts on Stan’s timestep adaptation over [here](https://discourse.mc-stan.org/t/issue-with-dual-averaging/5995/35) from @monnahc .

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