RISKPY / STANDALONE 1.0

Uncertainty.
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Excel workbook simulation

Use the uncertain-input distributions below to drive numeric cells in your Excel model. Link fixed assumptions if you want their table values applied during the run, then select the formula cells to record.

Role / nameExcel cell

Input and fixed cells must contain numbers. Output cells contain your Excel calculations. Unlinked workbook assumptions retain their existing values. Start with 100 trials; workbook recalculation is slower than Python models. This pilot excludes RISKPY formulas, volatile random/time formulas and external-workbook links in the model workbook. Save a copy before your first run; avoid editing the workbook while it runs.

Link inputs and at least one output, or create the batch example.

Extensive PDF user guide

01   Simulation

02   Uncertain inputs

NameDistribution

Fixed assumptions

NameValue
Input correlation

Monte Carlo only. The matrix must be symmetric, with ones on its diagonal. Rows follow the input order. This is the Gaussian copula's latent-normal correlation.

03   Your Python script

Write your own model, open an existing .py file, or edit a worked example. A script defines model(inputs, constants) and returns named output arrays.

Current script:

View or edit Python script

NumPy is available as np and SciPy distributions as stats. Inputs contain one value per trial. Opened files stay in the local add-in; Run simulation executes the script.