Simul8 Help Center features:distributions

Access Information Store

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:04+00:00

Access Information Store A spreadsheet contained in the Information Store can be accessed from the Distribution Dialog. Double click on the ??? question marks and browse to the spreadsheet. You can reference a fixed cell in the spreadsheet (eg. MySheet[1,1]) or use a variable to look up the cell (e.g. MySheet[x,y]).

Average Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:04+00:00

Average Distribution In simulations where little data is available to justify use of parametrized statistical distributions use the Average distribution. With this you only need to input your estimate of the average (mean) of the time (or other data).

Bernoulli Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:04+00:00

Bernoulli Distribution The Bernoulli distribution is a discrete distribution and with probability p the outcome is 0 while with probability 1-p it is 1 (Simul8 only asks for the former). The parameter is bound between 0 and 1. It is often used to include binary choices or outcomes of experiments in a simulation, for example whether a test was passed “Yes” or “No” and that stored in a Label can be used for later simulation logic. Similarly, it can be used for Routing Out decisions, again …

Beta Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:05+00:00

Beta Distribution The Beta Distribution is a very flexible distribution that can take a very wide variety of shapes including bells skewed in either direction, almost linear shapes that curve at the end and bells that stop at fixed limit rather than running out to infinity.

Binomial Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:05+00:00

Binomial Distribution The Binomial distribution is a discrete distribution which provides the number of successes in a specified number of trials of experiments with binary outcomes (0 or 1). The outcome 0 occurs with probability p and 1 with probability 1-p. Simul8 asks for the former and it can be used for instance to specify how many tests a Work Item has passed.

Bounded Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:05+00:00

Bounded Distribution The Bounded Distribution is simply a standard distribution that has additional upper and lower limits set. This prevents extreme or undesirable values being sampled. If the distribution is sampled and a value outwith the upper and lower range is sampled then the result is not used.

Combination Distributions

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:05+00:00

Combination Distributions A combination distribution adds together samples from a number of individual distributions. This can be used to create special shapes of distribution or to enable unusual circumstances to be added to normal performance.

Distribution Viewer

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:06+00:00

Distribution Viewer The Distribution Viewer gives a visual representation of your data and distribution. This will open as in the Named Distribution dialog when creating custom distributions. The histogram is drawn based on the distribution and parameters entered on the left-hand side of the dialog. Changing the distribution will update the…

Erlang Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:06+00:00

Erlang Distribution Erlang is a convolution of exponential samples. Thus Erlang 1 (K=1) is the same as exponential. Erlang 2 is a very left skewed bell chopped at 0. As K increases the shape moves towards normal but never samples < 0. In Simul8 it is commonly used for Mean-Time-To-Repair (MTTR) reflecting its common usage for that in manufacturing. Otherwise, it is used as an extension of the Exponential distribution for any sort of durations, such as between arrivals.

Exponential Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:06+00:00

Exponential Distribution (Also known as Negative Exponential) This is a classic distribution used for arrival times of anything where one arrival is independent of the next. Examples are customers arriving at a store, patients arriving at a hospital. Sometimes it is also relevant to breakdowns.

External Distributions

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:06+00:00

External Distributions External distributions allow Simul8 to collect timing information from other Windows packages, rather than simply using Simul8’s built-in statistical distributions. There are two types of external distributions that you can use: Excel and Visual Basic.

Fixed Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:07+00:00

Fixed Distribution A “Fixed” distribution is not a distribution! - it is a fixed value. A sample from this distribution will always return the value in the “Fixed Value” field. This facility enables randomness to be removed from an element of the simulation but also enables

Gamma Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:07+00:00

Gamma Distribution This is rarely used directly but it is an important distribution because it is used to generate other distributions that have much more use (e.g. Beta, Pearson etc). Similar shapes to Weibull. Unless your data closely matches gamma use weibull. Weibull is much faster to generate.

Geometric Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:07+00:00

Geometric Distribution The Geometric distribution is a discrete one and it provides the probability of a first success (in a series of experiments) requiring a certain number of independent trials, each with the same success probability p. Simul8 asks for this parameter between 0 and 1.

Label Based Distributions

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:07+00:00

Label Based Distributions A Label Based Distribution lets you place information about what distribution should be used for sampling in a Label attached to each Work Item. For example, if patients in a hospital all have to see a doctor, but the average time they spend with the doctor is dependent on their illness, then you can set up a Label (called, say,

Log Normal Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:08+00:00

Log Normal Distribution Often used for the time it will take to do a job. It is a bell shaped curve, skewed to the left. No samples can be less than zero. See Also * Other types of distributions in Simul8

Named Distributions

Anonymous (anonymous@undisclosed.example.com) — 2025-02-25T10:32:10+00:00

Named Distributions In Simul8 you can name distributions that can be applied in many places in simulations. For example, if you have a simulation with 50 machines that work at the same given rate but you need to change this rate, you could create a distribution named ‘MACHDIST’, apply the distribution to all machines, and easily update the distribution’s parameters.

Negative Binomial Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:08+00:00

Negative Binomial Distribution See Also * Other types of distributions in Simul8

Normal Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:08+00:00

Normal Distribution Symmetric bell shaped curve. This distribution is popular for setting timing and Label values as the likelihood of extreme high or low values is very low and can be controlled via the standard deviation. For instance, it is used for durations of operations when variability is low (e.g. operation usually takes 24 minutes but sometimes varies as low as 21 and as high as 27).

Pearson V Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:09+00:00

Pearson V Distribution See Also * Other types of distributions in Simul8

Pearson VI Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:09+00:00

Pearson VI Distribution See Also * Other types of distributions in Simul8

Poisson Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:09+00:00

Poisson Distribution See Also * Other types of distributions in Simul8

Probability Profile

Anonymous (anonymous@undisclosed.example.com) — 2025-04-03T10:47:57+00:00

Probability Profile A Probability Profile is a type of Distribution that sets the probability (the percentage chance) of a value being sampled from a distribution. Probability Profiles can be configured to generate any shape of Distribution desired . To create a Probability Profile Distribution go to the Build tab > Distributions > New > Probability Profile.

Rounded Uniform Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:10+00:00

Rounded Uniform Distribution See Also * Other types of distributions in Simul8

Distribution Summary

Anonymous (anonymous@undisclosed.example.com) — 2025-02-25T10:32:51+00:00

Distribution Summary The Distribution Summary allows all the Distributions in a simulation to be viewed in one grid. The grid is split into tabs at the top, depending on the type of Distribution. The Distribution Summary is accessed through the Distributions button menu the Build tab

Time Absolute Distributions

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:10+00:00

Time Absolute Distributions A time absolute distribute lets you specify when you want something to happen (rather than a more usual approach of specifying how long it will be from now until the next thing happens). This is particularly useful in situations where something happens at the same time (or about the same time) each day. For example, a mail drop may happen at around 8am and 2pm each day.

Time Dependent Distributions

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:10+00:00

Time Dependent Distributions In many situations the speed of a part of a system is related to the time of day. Time dependent distributions enable this to be simulated. Time dependent distributions are made up of a sequence of Named distributions. Create a named distribution for each different part of the day that can be identified as requiring a different underlying distribution.

Triangular Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:11+00:00

Triangular Distribution See Also * Other types of distributions in Simul8

Uniform Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:11+00:00

Uniform Distribution Samples from a uniform distribution are equally spread between the lower bound and the upper bound. The mean of the value sampled is half way between the two values specified. No sample values occur outside this range.

Weibull Distribution

Anonymous (anonymous@undisclosed.example.com) — 2025-02-12T09:36:11+00:00

Weibull Distribution This is a fairly flexible distribution that can take on quite a few shapes depending on its Alpha parameter. With Alpha <= 1 it has shapes similar to exponential, but >=2 the shape is more like a wide lognormal. See Also