Sampling subset of data.
samplingSubsetData.RdSampling subset of data.
Usage
samplingSubsetData(d = NULL, sampUnit = NULL, nperm = 9,
type = "proportion", prop = seq(10, 100, by = 10), MinSample = 1,
Size = NULL)Arguments
- d
Dataframe of data to sample. Each line is an individual.
- sampUnit
A Factor defining the sampling unit to impoverish. For example it can be the species or the plot attributes of each individual.
- nperm
Number of permutations.
- type
Type of sampling. Either proportion, count, propBySize or factorBySize. See details.
- prop
Integer between 1 and 100. Categorical proportions to sample in percentage.
- MinSample
Minimum number of individual to sample by sample unit. Default is one.
- Size
A vector of value for each individual (type propBySize and factorBySize) or for each level of factor (factorBySize only). Determine the rank of individual/factor when using the sampling schemes propBySize and factorBySize.
Details
Sampling scheme count sample a number of individuals wheras proportion sample a proportion of individuals by sample unit. Sampling scheme propBySize sample in each sampling unit (sampUnit) a proportion of the individual ranked using the argument Size. Consequently, the bigest individuals (higher Size) will be sample before the smaller one. factorBySize sample a proportion of sampling unit (sampUnit) ranked using the argument Size. For example you can sample only the individuals of the 20% of the more aboundant species.