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First, we computed the sample average variables for each household.
The proposed method makes use of the sample average approximation (SAA) method with statistical bounding techniques.
A solution approach integrating the sample average approximation scheme with an importance sampling strategy is developed.
Specifically, we assume that the sample average ¯¯¯X has a Johnson distribution.
When L is sufficiently large, the sample average value is used to approximate the expectation value.
MMSE Averaging: Calculate the sample average according to (19) which is the target state.
Finally the problem was solved by applying the sample average approximation algorithm.
The sample average of stock market returns is indicated by the red vertical line3.
At each iteration, the sample average approximation method is applied to the NLP sub-problem and MILP master problem.
A heuristics based on the sample average approximation, involving the Monte Carlo sampling methods, is proposed to solve the problem.
The proposed method adopts the sample average approximation (SAA) method for scenario generation and optimal gap statistical bounding.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com