Total Effect Centrality

Total Effect Centrality

Usage

TotalCentral(phi, delta_t)

Arguments

phi

Numeric matrix. The drift matrix (\(\boldsymbol{\Phi}\)). phi should have row and column names pertaining to the variables in the system.

delta_t

Vector of positive numbers. Time interval (\(\Delta t\)).

See also

Other Continuous Time Mediation Functions: DeltaBeta(), DeltaIndirectCentral(), DeltaMed(), DeltaTotalCentral(), Direct(), Indirect(), IndirectCentral(), MCBeta(), MCIndirectCentral(), MCMed(), MCPhi(), MCTotalCentral(), Med(), PosteriorBeta(), PosteriorIndirectCentral(), PosteriorMed(), PosteriorPhi(), PosteriorTotalCentral(), Total(), Trajectory()

Author

Ivan Jacob Agaloos Pesigan

Examples

phi <- matrix(
  data = c(
    -0.357, 0.771, -0.450,
    0.0, -0.511, 0.729,
    0, 0, -0.693
  ),
  nrow = 3
)
colnames(phi) <- rownames(phi) <- c("x", "m", "y")

# Specific time interval ----------------------------------------------------
TotalCentral(
  phi = phi,
  delta_t = 1
)
#> 
#> Total Effect Centrality
#> 
#>      interval   x      m y
#> [1,]        1 0.4 0.3998 0

# Range of time intervals ---------------------------------------------------
total_central <- TotalCentral(
  phi = phi,
  delta_t = 1:30
)
plot(total_central)


# Methods -------------------------------------------------------------------
# IndirectCentral has a number of methods including
# print, summary, and plot
total_central <- TotalCentral(
  phi = phi,
  delta_t = 1:5
)
print(total_central)
#> 
#> Total Effect Centrality
#> 
#>      interval      x      m y
#> [1,]        1 0.4000 0.3998 0
#> [2,]        2 0.7298 0.4398 0
#> [3,]        3 0.8855 0.3638 0
#> [4,]        4 0.8970 0.2683 0
#> [5,]        5 0.8204 0.1859 0
summary(total_central)
#>      interval      x      m y
#> [1,]        1 0.4000 0.3998 0
#> [2,]        2 0.7298 0.4398 0
#> [3,]        3 0.8855 0.3638 0
#> [4,]        4 0.8970 0.2683 0
#> [5,]        5 0.8204 0.1859 0
plot(total_central)