partition (version 0.1.0)

test_permutation: Permute partitions

Description

test_permutation() permutes data and partitions the results to generate a distribution of null statistics for observed information, number of clusters, and number of observed variables reduced to clusters. The result is a tibble with a summary of the observed data results and the averages of the permuted results. The partitions and and permutations are also available in list-cols. test_permutation() tests across a range of target information values, as specified in the information argument.

Usage

test_permutation(.data, information = seq(0.1, 0.6, by = 0.1),
  partitioner = part_icc(), ..., nperm = 100)

Arguments

.data

a data set to partition

information

a vector of minimum information to fit in partition()

partitioner

the partitioner to use. The default is part_icc().

...

arguments passed to partition()

nperm

Number of permuted data sets to test. Default is 100.

Value

a tibble with summaries on observed and permuted data (the means of the permuted summaries), as well as list-cols containing them

Examples

Run this code
# NOT RUN {
set.seed(123)
df <- simulate_block_data(c(3, 4, 5), lower_corr = .4, upper_corr = .6, n = 100)

test_permutation(df, partitioner = part_pc1(), nperm = 10)

# }

Run the code above in your browser using DataCamp Workspace