MetaLandSim-package     Landscape And Range Expansion Simulation
accept.calculate        Calculate acceptance rates in MCMC chains
addpoints               Add a given number of patches to a landscape
cabrera                 Modified patch occupancy data of Cabrera vole
calcmode                Function for mode estimation of a continuous
                        variable
cluster.graph           Delivers the number of patches per cluster
cluster.id              Classify patches in clusters
coda.create             Create files for use with R-package coda.
combine.chains          Combines two chains into a single chain.
components.graph        Number of components of a landscape
convert.graph           Convert data frame to landscape
create.parameter.df     Create parameter data frame
edge.graph              Produce an edge (links) data frame
expansion               Class 'expansion'
extract.graph           Extract landscape from span.graph generated
                        list
ifm.missing.MCMC        Estimate the 'missing' design incidence
                        function model
ifm.naive.MCMC          Estimate the naive design incidence function
                        model
ifm.robust.MCMC         Estimate the robust design incidence function
                        model
import.shape            Import a shapefile
iterate.graph           Simulate landscape series occupation
landscape               Class 'landscape'
landscape_change        Landscape loosing 5% of patches per time step
list.stats              Returning information on a dynamic landscape
                        list
manage_expansion_sim    Simulate range expansion simulation
manage_landscape_sim    Batch landscape simulation
matrix.graph            Returning a matrix with information on
                        connections between patches
mc_df                   Modified patch occupancy data of Cabrera vole
                        as a data frame
merge_order             Internal functions for the MetaLandSim package.
metapopulation          Class 'metapopulation'
metrics.graph           Computes landscape connectivity metrics
min_distance            Computes topological distance
occ.landscape           Sample landscape with one simulated occupancy
                        snapshot
occ.landscape2          Sample landscape with 10 simulated occupancy
                        snapshots
param1                  Sample parameter data frame number 1
param2                  Sample parameter data frame number 2
parameter.estimate      Estimate parameters
plotL.graph             Plot one landscape of the list created by
                        span.graph
plot_expansion          Graphical display of the expansion simulations
plot_graph              Graphical display of the landscape
range_expansion         Computes a range expansion model
range_raster            Probability of occupancy, dispersal model
remove.species          Remove the species occupancy from the landscape
removepoints            Remove a given number of patches from the
                        landscape
rg_exp                  List with range.expansion output
rland                   Random landscape
rland.graph             Creates random landscape graph
sim.area                Vector of the areas for each site; here, 100
                        sites
sim.det.20              Array corresponding to nsites x nyears x
                        nvisits
sim.distance            Distance matrix between sampling sites (nsite x
                        nsite).
simulate_graph          Simulate species occupancy in one dynamic
                        landscape
simulatedifm            Set of simulated data to use with the IFM
                        parameter estimation functions. The data were
                        generated using the code provided in "details".
span.graph              Simulate landscape dynamics over a number of
                        time steps
species.graph           Simulate landscape occupation
spom                    Stochastic Patch Occupancy Model
summary_landscape       Summarize 'landscape' class objects
summary_metapopulation
                        Summarize 'metapopulation' class objects
z.sim                   Occupancy data generated with perfect
                        detection.
z.sim.20                Occupancy data generated with perfect detection
                        with approximately 20% of data missing at
                        random.
z.sim.20.fa             Occupancy data containing false absences
