addpoly
(Package: PopGenReport) :
Function to add a polygon to a landscape
adds a polygon to a raster layer
● Data Source:
CranContrib
● Keywords:
● Alias: addpoly
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pops2genind
(Package: PopGenReport) :
Function converts pops to a genind object
converts pops into genind (to calculate Fst etc.)
● Data Source:
CranContrib
● Keywords:
● Alias: pops2genind
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addline
(Package: PopGenReport) :
Function to add lines to landscape
adds a line from x1 to x2 to a raster layer
● Data Source:
CranContrib
● Keywords:
● Alias: addline
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reproduction
(Package: PopGenReport) :
Function to execute reproduction on a pop data.frame
reproduction subprocess on single populations
● Data Source:
CranContrib
● Keywords:
● Alias: reproduction
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spautocor
(Package: PopGenReport) :
Spatial autocorrelation following Smouse and Pekall 1999
Global spatial autocorrelation is a multivariate approach combining all loci into a single analysis. The autocorrelation coefficient r is calculated for each pairwise genetic distance pairs for all specified distance classes. For more information see Smouse and Peakall 1999, Peakall et a. 2003 and Smouse et al. 2008.
● Data Source:
CranContrib
● Keywords:
● Alias: spautocor
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gd.kosman
(Package: PopGenReport) :
Individual genetic distance calculation based on Kosman & Leonhard 2005
Calculates pairwise genetic distances between all individuals using the individual genetic distance measure of Kosman and Leonard (2005). This function is similiar to the dist.codom in the package mmod. The two functions differ in their treatment of individuals with missing data. dist.codom omits individuals from the calculation of pairwise individual genetic distances while this function includes individuals with missing data. This is done by simply calculating the mean individual pairwise genetic distance over all loci for which there are values. Note that depending on your computers capabilities, you may run into memory errors when this function is used on datasets with large numbers of individuals (>1000). Additionally, the time for this function to run can be lengthy. Using a PC with a 3.5 GHz processor to calculate pairwise genetic distances between individuals with 36 diploid loci it took 0.3 seconds for 100 individuals, 5 seconds for 500 individuals, 21 seconds for 1000 individuals, 84 seconds for 2000 individuals, and 194 seconds for 3000 individuals.
● Data Source:
CranContrib
● Keywords:
● Alias: gd.kosman
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mutation
(Package: PopGenReport) :
Function to execute mutation on a pop data.frame
mutation subprocess on single populations
● Data Source:
CranContrib
● Keywords:
● Alias: mutation
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costdistances
(Package: PopGenReport) :
Calculates cost distances for a given landscape (resistance matrix)
calculates a cost distance matrix, to be used with run.popgensim
● Data Source:
CranContrib
● Keywords:
● Alias: costdistances
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performs Multiple Matrix Regression with Randomization analysis This method was implemented by Wang 2013 (MMRR function see references) and also by Sarah Goslee in package ecodist. lgrMMRR is a simple wrapper to have a more user friendly output.
● Data Source:
CranContrib
● Keywords:
● Alias: lgrMMRR
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init.popgensim
(Package: PopGenReport) :
Initialise a pops object fo a a popgen simulation
initialises a time-forward, agent-based and spatiallly explicit genetic population simulation
● Data Source:
CranContrib
● Keywords:
● Alias: init.popgensim
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providing 
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