# Generates a spatial design using Quasi-random numbers Generates a spatially balanced design for given inclusion probabilities over a grid of potential sampling locations ```r quasiSamp( n, dimension=2, study.area=NULL, potential.sites=NULL, inclusion.probs=NULL, randStartType=3, nSampsToConsider=25*n, nStartsToConsider=100*n) quasiSamp.raster( n, inclusion.probs, randStartType=3, nSampsToConsider=25*n, nStartsToConsider=100*n) quasiSamp.cluster( nCluster, clusterSize, clusterRadius, inclusion.probs=NULL, working.inclusion.probs=NULL, nSampsToConsider=c(25*nCluster,25*clusterSize), nStartsToConsider=100*c(nCluster, clusterSize), mc.cores=parallel::detectCores()-1) ``` ## Arguments - `n`: the number of samples to take. - `nCluster`: the number of clusters to sample. Only used when sampling sites in cluster groups. - `clusterSize`: the number of sites within each cluster to sample. - `clusterRadius`: the radius of each individual clusters. Sites within a cluster will be chosen so that they are at most a distance of clusterRadius from the cluster centre. Must be specified in metres (see `extract` and `buffer`). - `dimension`: the number of dimensions that the samples are located in. Equal to 2 for areal sampling. Care should be taken with large dimensions as:1) the number of potential sampling sites needed for effective coverage starts to explode (curse of dimensionality); and 2) the well-spaced behaviour of the Halton sequence starts to deteriorate (but this requires very very many dimensions to be problematic -- included as a warning here for largely academic reasons). - `study.area`: a numeric matrix with dimension columns. This defines the sampling area from where the sites are selected -- each row defines a vertex of the sampling area and the order of rows is such that the vertices are joined in order. The last vertex is joined to the first. If NULL (default), the study.area is defined to be the smallest (hyper-)rectangle that bounds the potential.sites. If potential.sites is also NULL (default), then the study area is taken to be the unit (hyper-)square. This argument is closely related to potential.sites. - `potential.sites`: a matrix (of size Nxdimension) of the spatial coordinates of the N sampling locations, of which n<

quasiSamp function