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Summarise Matrix Population Models

Source: R/summarise_mpms.R
summarise_mpms.Rd

Calculates and summarises various metrics from matrix population models (MPMs) including dimension (= age in Leslie matrices), lambda values, maximum fecundity values, maximum growth/survival transition probabilities, and minimum non-zero growth/survival transition probabilities

Usage

summarise_mpms(x)

Arguments

x

A compadreDB object containing matrix population models, typically in a format compatible with matA, matU, and matF functions.

Value

This function prints summaries of the following metrics:

  • lambda values: The lambda values (dominant eigenvalues) of the A matrices.

  • max F values: The maximum values from the F matrices.

  • max U values: The maximum values from the U matrices.

  • minimum non-zero U values: The minimum non-zero values from the U matrices.

See also

Other utility: plot_matrix()

Examples

mats <- rand_lefko_set(
  n = 10, n_stages = 5, fecundity = c(0, 0, 4, 8, 10),
  archetype = 4, output = "Type1"
)

summarise_mpms(mats)
#> Summary of matrix dimension:
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>       5       5       5       5       5       5 
#> Summary of lambda values:
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>  0.7308  1.0153  1.2574  1.1995  1.4075  1.4787 
#> 
#> Summary of maximum F values:
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>      10      10      10      10      10      10 
#> 
#> Summary of maximum U values:
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>  0.7040  0.9346  0.9833  0.9330  0.9860  0.9882 
#> 
#> Summary of minimum non-zero U values:
#>     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
#> 0.007748 0.014295 0.040216 0.049619 0.068094 0.134043