RCSample: Simulate A Random Continious Sampling of Equal Sizes.
In upi-qe/qualityr: Calculate Quality Statistics

Description Usage Arguments Value Examples

Simulate A Random Continious Sampling of Equal Sizes.

RCSample(base.pop, t.trials, n.sample, seed, norm.mean = NULL,
  norm.sd = NULL, exp.rate = NULL, log.location = NULL,
  log.scale = NULL, lnorm.mean = NULL, lnorm.sd = NULL,
  uni.min = NULL, uni.max = NULL, wei.shape = NULL,
  wei.scale = NULL)

`base.pop`	Define the desired continuos distribution to be sampled from. The function can handle any of the following continous distributions: "Normal", "Exponential", "Logistic", "Log Normal", "Uniform", & "Weibull".
`t.trials`	This defines the number of sampling points throughout the manufacturin process were a defined number of repeat samples, i.e. n.sample, will be taken. The total collection of trials is thought of as the measure of the processes reproducability. Unlike n.sample, t.trials may be a single number or a vector of numbers. For example, if only a single number is provided, e.g. 1, its assumed that there is only one instance where n.sample is executed and the t.trials is essentially ignored; better thought of as pulling a large random sampling to approximate the underlying population. However, if a vector of numbers is provided, e.g. 1:5, the output assumes that for the 1st though the 5th trials n.samples will be drawn for approximating the processes repeatability and reproducability. In addition, one could set this to a delayed sampling, e.g. 6:10, where shifts in the manufacturing process may occur and t.trials from 1:5 can be combined with the output from 6:10 to craete population shifts.
`n.sample`	On each sampling trial, i.e. t.trail, this is the number of repeat samples to be taken and is thought of as the measure of the processes repeatability at that moment in time. Only a single number may be used and it is assumed that equal proporation sampling will be done on each trial with this sample size.
`seed`	Becuase this is a simulation of random numbers, a random number generator is used and a "seed" is specified for reproducability. This is used to set the "set.seed" function from the "base" package. See documention around the "set.seed" function for more details.
`norm.mean`	One of two paramaters requried for the "rnorm" function in the "stats" package. See documention around the "rnorm" function for more details. Normal Distribution random sampling.
`norm.sd`	One of two paramaters requried for the "rnorm" function in the "stats" package. See documention around the "rnorm" function for more details.Normal Distribution random sampling.
`exp.rate`	Single paramater requried for the "rexp" function in the "stats" package. See documention around the "rexp" function for more details. Exponential Distribution random sampling.
`log.location`	One of two paramaters requried for the "rlogis" function in the "stats" package. See documention around the "rlogis" function for more details. Logistic Distribution random sampling.
`log.scale`	One of two paramaters requried for the "rlogis" function in the "stats" package. See documention around the "rlogis" function for more details. Logistic Distribution random sampling.
`lnorm.mean`	One of two paramaters requried for the "rlnorm" function in the "stats" package. See documention around the "rlnorm" function for more details. Log Normal Distribution random sampling.
`lnorm.sd`	One of two paramaters requried for the "rlnorm" function in the "stats" package. See documention around the "rlnorm" function for more details. Log Normal Distribution random sampling.
`uni.min`	One of two paramaters requried for the "runif" function in the "stats" package. See documention around the "runif" function for more details. Uniform Distribution random sampling.
`uni.max`	One of two paramaters requried for the "runif" function in the "stats" package. See documention around the "runif" function for more details. Uniform Distribution random sampling.
`wei.shape`	One of two paramaters requried for the "rweibull" function in the "stats" package. See documention around the "rweibull" function for more details. Weibull Distribution random sampling.
`wei.scale`	One of two paramaters requried for the "rweibull" function in the "stats" package. See documention around the "rweibull" function for more details. Weibull Distribution random sampling.

A tibble, i.e. data frame, consiting of the result from the paramaters of base.pop, n.sample, t.trails, seed, and the necessary paramaters for the desired continuose populatoins.

RCSample(base.pop = "Normal", t.trials = 1, n.sample = 100, seed = 647, norm.mean = 100, norm.sd = 10)
RCSample(base.pop = "Normal", t.trials = 1:10, n.sample = 30, seed = 52, norm.mean = 100, norm.sd = 10)
RCSample(base.pop = "Exponential", t.trials = 3:5, n.sample = 5, seed = 12345, exp.rate = 0.5)
RCSample(base.pop = "Logistic", t.trials = 1:5, n.sample = 10, seed = 89, log.location = 0, log.scale = 1)
RCSample(base.pop = "Log Normal", t.trials = 1:30, n.sample = 15, seed = 10, lnorm.mean = 10, lnorm.sd = 2)
RCSample(base.pop = "Uniform", t.trials = 8:9, n.sample = 25, seed = 872, uni.min = 0, uni.max = 10)
RCSample(base.pop = "Weibull", t.trials = 1:100, n.sample = 7, seed = 2, wei.shape = 10, wei.scale = 5)