draw_sample_n: Sample data close to desired characteristics - nearest

In drawsample: Draw Samples with the Desired Properties from a Data Set

Sample data close to desired characteristics - nearest

Description

A Function to sample data close to desired characteristics - nearest

Usage

draw_sample_n(
  dist,
  n,
  skew,
  kurts,
  location = 0,
  delta_var = 0,
  save.output = FALSE,
  output_name = c("sample", "default")
)

Arguments

dist	data frame:consists of id and scores with no missing
n	numeric: desired sample size
skew	numeric: the skewness value
kurts	numeric: the kurtosis value
location	numeric: the value for adjusting mean (default is 0).
delta_var	numeric: the value for adjusting variance (default is 0).
save.output	logical: should the output be saved into a text file? (Default is FALSE).
output_name	character: a vector of two components. The first component is the name of the output file, user can change the second component.

Details

The desired skewness and kurtosis values cannot be met while the function execution is faster. The attributes of kurtosis are in doubt. This is because the range of kurtosis is greater than the skewness. For location values can be entered to position the midpoint or mean of the distribution differently. For delta_var the value can be entered for how much will increase or decrease the variability of reference distribution. In other words, the reference distribution is generated as the standard normal distribution, unless the user changes the default values of the location and delta_var arguments.

Value

This function returns a list including following:

• a matrix: Descriptive statistics of the given data, the reference vector and the sample.

• a data frame: The id's and scores of the sample

• graph: Histograms for the “data” and the “sample”

References

Fleishman AI (1978). A Method for Simulating Non-normal Distributions. Psychometrika, 43, 521-532. doi: 10.1007/BF02293811.

Fialkowski, A. C. (2018). SimMultiCorrData: Simulation of Correlated Data with Multiple #' Variable Types. R package version 0.2.2. Retrieved from https://cran.r-project.org/web/packages/SimMultiCorrData/index.html

Examples

# Example data provided with package
data(example_data)
# Draw a sample based on Score_1
output2 <- draw_sample_n(dist=example_data[,c(1,2)],n=200,skew = 0,
kurts = 0, location=0, delta_var=0,save.output=FALSE) # Histogram of the reference data set
# descriptive statistics of the given data,reference data, and drawn sample
output2$desc
# First 6 rows of the drawn sample
head(output2$sample)
# Histogram of the given data set and drawn sample
output2$graph
## Not run: 
# Draw a sample based on Score_2 (location par)
# draw_sample_n(dist=example_data[,c(1,3)],n=200,skew = 1,kurts = 1,location=-0.5,delta_var=0,
# save.output=TRUE, output_name = c("sample", "2"))
# Draw a sample based on Score_2 (delta_var par)
# draw_sample_n(dist=example_data[,c(1,3)],n=200,skew = 0.5,kurts = 0.4,location=0,delta_var=0.3,
# save.output=TRUE, output_name = c("sample", "3"))

## End(Not run)

drawsample documentation built on Sept. 6, 2022, 1:06 a.m.