partboot: Partial Bootstrapped Semantic Network Analysis

Description Usage Arguments Value Author(s) Examples

View source: R/partboot.R

Description

Bootstraps (without replacement) the nodes in the network and computes global network characteristics

Usage

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partboot(data, paired = NULL, n, weighted = FALSE, iter = 1000,
  corr = c("cor", "cosine"), cores, seeds = NULL)

Arguments

data

Cleaned response matrix

paired

Should bootstrapped nodes be paired? Defaults to NULL. Input a matrix, data frame or list containing another sample

n

Number of nodes for bootstrap. Defaults to round(ncol(data)/2,0) (i.g., 50% of nodes)

weighted

Should weighted ASPL and CC be used? Defaults to FALSE. Set to TRUE for weighted ASPL and CC

iter

Number of iterations in bootstrap. Defaults to 1000

corr

Association method to use. Defaults to "cosine"

cores

Number of computer processing cores to use for bootstrapping samples. Defaults to n - 1 total number of cores. Set to any number between 1 and maxmimum amount of cores on your computer

seeds

Seeds used in previous run. Defaults to NULL. Input a vector from previous run to replicate analyses

Value

Returns a list that includes the original semantic network measures (origmeas; ASPL, CC, Q, S), the bootstrapped semantic network measures (bootmeas), and Seeds that can be used to replicate analysis

Author(s)

Alexander Christensen <[email protected]>

Examples

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#finalize rmatA
finalCmat <- finalize(convmat)
#finalize rmatB
finalRmat <- finalize(rmat)

#equate rmatA and rmatB
eq1 <- equate(finalCmat,finalRmat)

#obtain respective equated response matrices
eqCmat <- eq1$rmatA
eqRmat <- eq1$rmatB


results <- partboot(eqCmat, eqRmat, iter = 10, corr = "cosine", cores = 4)

AlexChristensen/SemNetToolbox documentation built on Aug. 7, 2018, 6:02 p.m.