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Correlation Matrix - cov

This sheet defines correlation structure for multiplier draws, and optionally for organization-specific noise when using the vertical format.

Accepted Formats

The parser accepts two formats.

Matrix Format

Example:

Impact Multiplier Hedginess FundingAdditionality ActivityAdditionality
Hedginess 1.0
FundingAdditionality 0.3 1.0
ActivityAdditionality -0.1 0.0 1.0

Rules:

  • The first column should be named Impact Multiplier.
  • Row and column labels are normalized by removing spaces and dots.
  • Lower-triangle-only input is acceptable; the parser symmetrizes the matrix.
  • Missing pairs default to 0.
  • Missing multipliers are allowed; unrecognized names are filtered out.

Vertical Format

Example:

Variable1 Variable2 Correlation Type
Hedginess FundingAdditionality 0.3 Multiplier
FundingAdditionality Hedginess 0.3 Multiplier
OrgA OrgB 0.5 Noise

Rules:

  • Required columns are Variable1, Variable2, and Correlation.
  • Type is optional. If omitted, the parser assumes Multiplier.
  • Valid Type values are Multiplier and Noise.
  • Noise rows are only used if organization names are available from the rest of the input.

See Noise And Model Coverage for how Type = Noise correlations are used after expected values are computed.

Parser Behavior

The current implementation:

  • Detects the format automatically.
  • Removes duplicate row or column names in matrix format, keeping the first occurrence and recording an error.
  • Removes duplicate (Variable1, Variable2) pairs in vertical format, keeping the first occurrence and recording an error.
  • Makes correlations symmetric by copying (A, B) to (B, A) when needed.
  • Completes any missing pairs with 0.
  • Returns an identity-like fallback for multiplier correlations if parsing fails badly enough to produce no matrix.

Safer Authoring Conventions

To keep docs and spreadsheets predictable:

  • Prefer explicit 1 values on the diagonal.
  • Prefer lower-triangle matrix input or explicitly symmetric vertical input.
  • Use vertical format if you need Noise correlations between organizations.
  • Keep names aligned with normalized multiplier and organization names used elsewhere in the workbook.

Notes For Agents

  • The cov sheet is read after imp and before fos/orgmeta are fully combined, but multiplier correlation is finalized only once the engine knows the final multiplier set.
  • Formula-generated multipliers can extend the final multiplier correlation matrix later; newly added formula multipliers get zero correlation with other multipliers by default.
  • The Shiny preview can display either observed correlations from simulated draws or the input correlations from this sheet.