| sumstat_tajimas_d {coala} | R Documentation | 
Summary Statistic: Tajima's D
Description
This statistic calculates Tajima's D from the simulation results when added to a model. Tajima's D primarily measures an deviation of singletons from the neutral expectation of an equilibrium model. Negative values indicate an excess of singletons, while positive values code a depletion of them.
Usage
sumstat_tajimas_d(
  name = "tajimas_d",
  population = "all",
  transformation = identity
)
Arguments
name | 
 The name of the summary statistic. When simulating a model, the value of the statistics are written to an entry of the returned list with this name. Summary statistic names must be unique in a model.  | 
population | 
 The population for which the statistic is calculated. Can also be "all" to calculate it from all populations. Default is population 1.  | 
transformation | 
 An optional function for transforming the results of the statistic. If specified, the results of the transformation are returned instead of the original values.  | 
Value
On simulation, this returns a vector with the value of Tajima's D for each locus.
References
Tajima, F. (1989). "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.". Genetics 123 (3): 585-95.
See Also
To create a demographic model: coal_model
To calculate this statistic from data: calc_sumstats_from_data
Other summary statistics: 
sumstat_dna(),
sumstat_file(),
sumstat_four_gamete(),
sumstat_ihh(),
sumstat_jsfs(),
sumstat_mcmf(),
sumstat_nucleotide_div(),
sumstat_omega(),
sumstat_seg_sites(),
sumstat_sfs(),
sumstat_trees()
Examples
# A neutral model that should yield values close to zero:
model <- coal_model(5, 2) +
  feat_mutation(20) +
  feat_recombination(10) +
  sumstat_tajimas_d("taji_d")
stats <- simulate(model)
print(stats$taji_d)