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Copy file name to clipboardExpand all lines: src/alg_traits.jl
+6-5Lines changed: 6 additions & 5 deletions
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@@ -245,16 +245,17 @@ function alg_order(alg::AbstractODEAlgorithm)
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end
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"""
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Integral interpolation for the SDE solver algorithm. SDEs solutions depend on the chosen definition of the stochastic integral. In the Ito calculus,
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the left-hand rule is taken, while Stratonovich calculus uses the right-hand rule. Unlike in standard Riemannian integration, these integral rules do
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not converge to the same answer. In the context of a stochastic differential equation, the underlying solution (and its mean, variance, etc.) is dependent
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on the integral rule that is chosen. This trait describes which interpretation the solver algorithm subscribes to, and thus whether the solution should
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Integral interpolation for the SDE solver algorithm. SDEs solutions depend on the chosen definition of the stochastic integral. In the Ito calculus,
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+
the left-hand rule is taken, while Stratonovich calculus uses the right-hand rule. Unlike in standard Riemannian integration, these integral rules do
250
+
not converge to the same answer. In the context of a stochastic differential equation, the underlying solution (and its mean, variance, etc.) is dependent
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+
on the integral rule that is chosen. This trait describes which interpretation the solver algorithm subscribes to, and thus whether the solution should
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be interpreted as the solution to the SDE under the Ito or Stratonovich interpretation.
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For more information, see https://oatml.cs.ox.ac.uk/blog/2022/03/22/ito-strat.html as a good high-level explanation.
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!!! note
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The expected solution statistics are dependent on this output. Solutions from solvers with different
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The expected solution statistics are dependent on this output. Solutions from solvers with different
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interpretations are expected to have different answers on almost all SDEs without additive noise.
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