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Table 1 Required system integrations, equations used, and sources of error.

From: A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems

Method System Integrations ROSA SOSA Equations Used Error Sources
MC 2L(J + 1) 264000 288000 (10)-(12) • number of MC samples used
DA 2J(J + 1) + 1 925 1105 (14)-(16) • local approximation
      • truncation of Taylor series
      • derivative approximation
PA J(J - 1)S2/2 + JS + 1 3445 4141 (14), (15), (18) • local approximation
      • truncation of FD-HDMR
      • polynomial approximation
      • polynomial regression
GHI 2J(J - 1)Q/22 + 2JQ/2 + 1 3445 4141 (14), (15), (19)-(21) • local approximation
      • truncation of FD-HDMR
      • Gauss-Hermite integration
OHA L 6000 6000 (14), (15), (23) • truncation of ANOVA-HDMR
      • Hermite approximation
      • polynomial regression
  1. L: number of Monte Carlo (Latin hypercube) samples.
  2. J: number of biochemical factors.
  3. S: number of regression samples per factor.
  4. Q: order of Gauss-Hermite integration.