# Nelder Mead tolerance vastly higher when I restart optimization with updated guess for initial parameters

**URL:** <https://discourse.julialang.org/t/nelder-mead-tolerance-vastly-higher-when-i-restart-optimization-with-updated-guess-for-initial-parameters/87939>\
**Category:** General Usage\
**Tags:** statistics, optim, optimization\
**Created:** [September 28, 2022, 3:17pm UTC](https://discourse.julialang.org/t/nelder-mead-tolerance-vastly-higher-when-i-restart-optimization-with-updated-guess-for-initial-parameters/87939 "2022-09-28T15:17:59Z")\
**Posts on this page:** 1\
**Page:** 2

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**Author:** ![stevengj](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/stevengj/32/71_2.png) [@stevengj](https://discourse.julialang.org/u/stevengj)\
**Post date:** [October 1, 2022, 3:32pm UTC](https://discourse.julialang.org/t/nelder-mead-tolerance-vastly-higher-when-i-restart-optimization-with-updated-guess-for-initial-parameters/87939/21 "2022-10-01T15:32:40Z")

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> [@structural](#):
>
> Which gradient free alternative would you recommend?

I usually start with one of Powell’s methods, like BOBYQA, or the related quasi-Newton methods by Andy Conn.

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