cor_data: cor_data

In sigbertklinke/exams2moodle: Access routines to XML Moodle files and helper routines to simplify generating exercises for Moodle from the 'exams' package

cor_data

Description

Generates a data set based on 'xandy⁠for a given target correlation⁠r⁠according to [stats::cor()]. The algorithm modifies the order of the⁠y⁠'s, therefore is guaranteed that the (marginal) distribution of ⁠x and y is not modified. Note that is not guaranteed that the final correlation is the desired correlation; the algorithm iteratively modifies the order. If you are unsatisfied with result it may help to increase maxit.

Usage

cor_data(
  x,
  y,
  r,
  method = c("pearson", "kendall", "spearman"),
  ...,
  maxit = 1000
)

Arguments

x	numeric: given x values
y	numeric: given y values
r	numeric: desired correlation
method	character: indicating which correlation coefficient is to be computed (default: '"pearson")
...	further parameters given to stats::cor()
maxit	numeric: maximal number of iterations (default: 1000)

Value

a matrix with two columns and an attribute interim for intermediate values as matrix. The rows of the matrix contain

• if method=="pearson": x_i, y_i, x_i-bar{x}, y_i-\bar{y}, (x_i-bar{x})^2, (y_i-\bar{y})^2, and (x_i-bar{x})((y_i-\bar{y}).

• if method=="kendall":

• if method=="spearman": x_i, y_i, p_i (concordant pairs), and q_i (disconcordant pairs). In a final step a vector with the row sums is appended as further column.

Examples

x <- runif(6)
y <- runif(6)
xy <- cor_data(x, y, r=0.6)
cbind(x, y, xy)

sigbertklinke/exams2moodle documentation built on July 6, 2023, 3:26 p.m.