| name | pra-monte-carlo |
| description | Run Monte Carlo (or fast Second Moment) schedule/cost risk simulations with the PRA package. Use when a user provides task-level uncertainty distributions and needs the range of possible project outcomes — mean, standard deviation, and P5/P50/P95 percentiles — optionally accounting for task correlation.
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When to use
- Task-level uncertainty can be described with probability distributions.
- The user needs percentile-based estimates (P50, P80, P95) for budgeting or
scheduling, or a confidence level for a cost/schedule target.
- Tasks may be correlated and you need to capture joint uncertainty.
If only first and second moments (means and variances) are available, or a
rapid analytical estimate is enough, use the Second Moment Method instead.
MCP tools
mcs_tool(num_sims, task_dists_json, cor_mat_json) — full Monte Carlo
simulation. num_sims is typically 10000.
smm_tool(mean_json, var_json, cor_mat_json) — fast analytical estimate of
total mean and variance from task means and variances.
task_dists_json is a JSON array of task distribution objects:
[{"type":"normal","mean":10,"sd":2},
{"type":"triangular","a":5,"b":10,"c":15},
{"type":"uniform","min":8,"max":12}]
- normal:
mean, sd
- triangular:
a (min), b (max), c (mode) — most common in practice
- uniform:
min, max
cor_mat_json is an optional JSON 2-D array; use "null" (or omit) for
independent tasks. Ignoring positive correlation underestimates total variance.
Interpreting results
- P50 (median): value with a 50% chance of being exceeded.
- P80: common contingency-budgeting threshold.
- P95: high-confidence estimate for management reserve / worst case.
- Mean may differ from P50 for skewed distributions.
Use at least 10,000 simulations for stable tail percentiles.
Follow-ups
contingency_tool for a reserve buffer (skill: pra-sensitivity-contingency).
sensitivity_tool to find the dominant risk drivers.
References
- GAO Cost Estimating and Assessment Guide (GAO-20-195G), Ch. 12.
- RAND, Quantitative Risk Analysis for Project Management (WR-112).