Produce a summary of a MAR model
summary.MAR.RdMethod for producing a summary of an object of class MAR. Calculates the number of zero, non-zero, positive, and negative coefficients in the best-fit and bootstrapped models, gives the AIC, BIC, and summary of the R^2 values for the models, and lists the calculated stability statistics associated with the models.
Usage
# S3 method for MAR
summary(object,...)Examples
data(L4.mar)
myvar <- c(0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2)
myres <- matrix(0.5,
nrow = length(which(myvar == 1)),
ncol = length(which(myvar != 0))
)
small <- L4.mar[1:20,]
run1 <- run.mar(small, variables = myvar, restrictions = myres, search = "random", boot = FALSE)
#>
#>
#> searching for best-fit model...
#> ...BEST-FIT MODEL SELECTED
#> ( search time: 0 minutes 5 seconds )
#>
#>
#>
#> identifying 10 lowest AIC models...
#> ...TOP MODELS RETAINED
#>
#> ════════════════════════════════════════════════════════════════════════════════
#>
#>
summary(run1)
#>
#> Matrix Coefficients:
#>
#> B C Total
#> total.coef 9 3 12
#> zeros 7 3 10
#> nonzeros 2 0 2
#> positive 1 0 1
#> negative 1 0 1
#>
#>
#> Information Criteria:
#>
#> AIC 134.5006
#> BIC 144.8894
#>
#>
#> R^2 Values:
#>
#> R2 R2_D
#> min 0 0.44
#> 1st qu 0 0.45
#> median 0 0.45
#> mean 0.16 0.46
#> 3rd qu 0.24 0.47
#> max 0.48 0.49
#>
#>
#> Stability:
#>
#> ATTRIBUTE METRIC VALUE
#> resilience detB 0.00
#> resilience maxeigB 0.51
#> resilience maxeigkrB 0.26
#> reactivity sigma.over.Vinf -0.76
#> reactivity maxeigBxB 0.17
#>
#>