# getDist: Random Observations Generator In SNSchart: Sequential Normal Scores in Statistical Process Management

## Description

Random observations generator selected from several distributions with user defined mean and variance.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```getDist( n, dist, mu, sigma, par.location = 0, par.scale = 1, par.shape = 1, dist.par = NULL, rounding.factor = NULL ) ```

## Arguments

 `n` scalar. Number of observations to be generated. `dist` character string. Select from: "Uniform: Continuous Uniform distribution . "Normal": Normal distribution (default). "Normal2": Squared Normal distribution (also known as Chi-squared). "DoubleExp": Double exponential distribution (also known as Laplace distribution). "DoubleExp2": Double exponential squared distribution from a `DoubleExp(0,1)`. "LogNormal": Lognormal distribution. "Gamma": Gamma distribution. "Weibull": Weibull distribution. "t": Student-t distribution. `mu` scalar. Expected value of the desired distribution. `sigma` scalar. Standard deviation of the desired distribution. `par.location` scalar. Location parameter of the desired distribution. Default 0**. `par.scale` scalar. Scale parameter of the desired distribution. Default 1**. `par.shape` scalar. Shape parameter of the desired distribution, Default 1. `dist.par` vector. Overwrite `par.location`, `par.scale`, `par.shape`. Depends on the distribution (default `NULL`): "Uniform: no matter how is defined always gives numbers between 0 and 1. "Normal": c(location, scale). "Normal2": c(location, scale). "DoubleExp": c(location, scale). "DoubleExp2": c(location, scale). "LogNormal": c(location, scale). "Gamma": c(scale, shape). "Weibull": c(shape, scale). "t": c(degrees of freedom). `rounding.factor` scalar. positive value that determine the range between two consecutive rounded values.

## Value

A vector `x` with `n` observations generated following the selected distribution with its parameters.

## **Note

• For "Lognormal", `par.location` and `par.scale` correspond to the location and scale parameters of the normal distribution that generales the lognormal. Hence, in this case they are the logmean and the logsigma parameters

• For "Normal2" and "DoubleExp2", `par.location` and `par.scale` correspond correspond to the location and scale parameters of the normal and double exponential that are used to generates their squared forms.

## Examples

 `1` ```getDist(1, "Normal", 0, 1) ```

SNSchart documentation built on April 7, 2021, 9:07 a.m.