Distributions

You can manually specify the probability distribution for any field by opening the Specify Parameters dialog box for that field, selecting the desired distribution from the Distribution list, and entering the distribution parameters in the Distribution parameters table. Following are some notes on particular distributions:

Categorical. The categorical distribution describes an input field that has a fixed number of numeric values, referred to as categories. Each category has an associated probability such that the sum of the probabilities over all categories equals one.
Note: If you specify probabilities for the categories that do not sum to 1, you will receive a warning.
Negative Binomial - Failures. Describes the distribution of the number of failures in a sequence of trials before a specified number of successes are observed. The parameter Threshold is the specified number of successes and the parameter Probability is the probability of success in any given trial.
Negative Binomial - Trials. Describes the distribution of the number of trials that are required before a specified number of successes are observed. The parameter Threshold is the specified number of successes and the parameter Probability is the probability of success in any given trial.
Range. This distribution consists of a set of intervals with a probability assigned to each interval such that the sum of the probabilities over all intervals equals 1. Values within a given interval are drawn from a uniform distribution defined on that interval. Intervals are specified by entering a minimum value, a maximum value and an associated probability.
For example, you believe that the cost of a raw material has a 40% chance of falling in the range of $10 - $15 per unit, and a 60% chance of falling in the range of $15 - $20 per unit. You would model the cost with a Range distribution consisting of the two intervals [10 - 15] and [15 - 20], setting the probability associated with the first interval to 0.4 and the probability associated with the second interval to 0.6. The intervals do not have to be contiguous and they can even be overlapping. For example, you might have specified the intervals $10 - $15 and $20 - $25 or $10 - $15 and $13 - $16.
Weibull. The parameter Location is an optional location parameter, which specifies where the origin of the distribution is located.

The following table shows the distributions that are available for custom distribution fitting, and the acceptable values for the parameters. Some of these distributions are available for custom fitting to particular storage types, even though they are not fitted automatically to these storage types by the Simulation Fitting node.

Table 1. Distributions available for custom fitting
Distribution	Storage type supported for custom fitting	Parameters	Parameter limits	Notes
Bernoulli	Integer, real, datetime	Probability	0 ≤ `Probability` ≤ 1
Beta	Integer, real, datetime	Shape 1 Shape 2 Minimum Maximum	≥ 0 ≥ 0 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Binomial	Integer, real, datetime	Number of trials (n) Probability Minimum Maximum	> 0, integer 0 ≤ `Probability` ≤ 1 < `Maximum` > `Minimum`	Number of trials must be an integer. Minimum and maximum are optional.
Categorical	Integer, real, datetime, string	Category name (or label)	0 ≤ `Value` ≤ 1	Value is the probability of the category. The values must sum to 1, otherwise a warning is generated.
Dice	Integer, string	Sides	2 ≤ `Sides` ≤ 20	The probability of each category (side) is calculated as 1/N, where N is the number of sides. The probabilities cannot be edited.
Empirical	Integer, real, datetime			You cannot edit the empirical distribution, or select it as a type. The Empirical distribution is only available when there is historical data.
Exponential	Integer, real, datetime	Scale Minimum Maximum	> 0 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Fixed	Integer, real, datetime, string	Value		You cannot specify the Fixed distribution for every field. If you want every field in your generated data to be fixed, you can use a User Input node followed by a Balance node.
Gamma	Integer, real, datetime	Shape Scale Minimum Maximum	≥ 0 ≥ 0 < `Maximum` > `Minimum`	Minimum and maximum are optional. Distribution uses a rate parameter, with a shape parameter α = k and an inverse scale parameter β = 1/θ.
Lognormal	Integer, real, datetime	Shape 1 Shape 2 Minimum Maximum	≥ 0 ≥ 0 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Negative Binomial - Failures	Integer, real, datetime	Threshold Probability Minimum Maximum	≥ 0 0 ≤ `Probability` ≤ 1 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Negative Binomial - Trials	Integer, real, datetime	Threshold Probability Minimum Maximum	≥ 0 0 ≤ `Probability` ≤ 1 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Normal	Integer, real, datetime	Mean Standard deviation Minimum Maximum	≥ 0 > 0 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Poisson	Integer, real, datetime	Mean Minimum Maximum	≥ 0 < `Maximum` > `Minimum`	Minimum and maximum are optional.
Range	Integer, real, datetime	Begin(X) End(X) Probability(X)	0 ≤ `Value` ≤ 1	X is the index of each bin. The probability values must sum to 1.
Triangular	Integer, real, datetime	Mode Minimum Maximum	`Minimum` ≤ `Value` ≤ `Maximum` < `Maximum` > `Minimum`
Uniform	Integer, real, datetime	Minimum Maximum	< `Maximum` > `Minimum`
Weibull	Integer, real, datetime	Rate Scale Location Minimum Maximum	> 0 > 0 ≥ 0 < `Maximum` > `Minimum`	Location, maximum and minimum are optional.