CV_Range: Change variance of distribution while keeping the mean...

In LDLcalc: Calculate and Predict the Low Density Lipoprotein Values

Change variance of distribution while keeping the mean constant

Description

Takes as input a vector of values that have a distribution with a variance expressed as coefficient of variation (CV), It then modifies the distribution, so that the CV changes from a lower bound (lower_CV_bound) to an upper bound (upper_CV_bound), while the mean stays constant. Optionally, it can also plot the resulting variances.

Usage

CV_Range(
  sampleVector,
  lower_CV_Bound,
  upper_CV_Bound,
  maxRandIter = 10000,
  plot = F
)

Arguments

sampleVector	The vector containing the initial values with initial distribution and CV
lower_CV_Bound	The lower CV value we wish the distribution to achieve.
upper_CV_Bound	The upper CV value we wish the distribution to achieve.
maxRandIter	The function uses a stochastic algorithm to change the CV values from the lower to the upper value desired. If these bounds have not been achieved after maxRandIter iterations (default=10000), the function will exit, in order to avoid a possible infinite loop.
plot	If set to TRUE, will plot the resulting variances (default=FALSE)

Value

A data frame where each column contains a distribution of values with increasing CV, from the lower bound to upper bound.

Examples

## Not run: 
DataFrame=CV_Range(sampleA$LDL,0,100,maxRandIter = 100, plot=TRUE)

## End(Not run)

LDLcalc documentation built on May 31, 2022, 5:07 p.m.