Data Engineering and BI courses are free this week!
The function GRF()
generates random frequencies based on a design, i.e.,
a list giving the factors and the categories with each factor.
The data are given in the compiled format.
GRF( design, n, prob = NULL, f = "Freq" )a data frame containing frequencies per cells of the design.
A list with the factors and the categories within each.
How many simulated participants are to be classified.
(optional) the probability of falling in each cell of the design.
(optional) the column names that will contain the frequencies.
The name of the function GRF() is derived from grd(),
a general-purpose tool to generate random data ch19ANOFA now bundled
in the superb package cgh21ANOFA.
# The first example disperse 20 particants in one factor having
# two categories (low and high):
design <- list( A=c("low","high"))
GRF( design, 20 )
# This example has two factors, with factor A having levels a, b, c:
design <- list( A=letters[1:3], B = c("low","high"))
GRF( design, 40 )
# This last one has three factors, for a total of 3 x 2 x 2 = 12 cells
design <- list( A=letters[1:3], B = c("low","high"), C = c("cat","dog"))
GRF( design, 100 )
# To specify unequal probabilities, use
design <- list( A=letters[1:3], B = c("low","high"))
GRF( design, 100, c(.05, .05, .35, .35, .10, .10 ) )
# The name of the column containing the frequencies can be changes
GRF( design, 100, f="patate")
Run the code above in your browser using DataLab