Distribution Pattern Dialog: Difference between revisions
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The Distribution Pattern Dialog enables values and times with random variation to be generated. For example the time a Multi-server takes to handle an item, or the inter-arrival time of items produced at an Entry. | The Distribution Pattern Dialog enables values and times with random variation to be generated. For example the time a Multi-server takes to handle an item, or the inter-arrival time of items produced at an Entry. | ||
Distributions are listed on the left. Fields appear depending on the distribution selected. | Distributions are listed on the left. Fields appear depending on the distribution selected. | ||
All distributions also include a truncation/rounding option button and a final scaling factor. Truncation/rounding is applied first, then scaling on the resulting number. | All distributions also include a truncation/rounding option button and a final scaling factor. Truncation/rounding is applied first, then scaling on the resulting number. | ||
Truncation/rounding is useful where specific values are needed, for example when using a distribution to select between options.<br> | |||
Scaling is useful where the distribution might not change but needs to be adapted in continuous or batch processing situations. | |||
{| cellspacing="1" cellpadding="1" border="1" style="width: 446px; height: 506px;" | {| cellspacing="1" cellpadding="1" border="1" style="width: 446px; height: 506px;" | ||
|- | |- | ||
| Fixed Value | | Fixed Value | ||
| Value | | Value | ||
| No variation, returns a single value. | | No variation, returns a single value. | ||
|- | |- | ||
| Equally Likely | | Equally Likely | ||
| Mean<br>Range */- | | Mean<br>Range */- | ||
| Uniformly distributed values centred on the mean. | | Uniformly distributed values centred on the mean. | ||
|- | |- | ||
| Equally Likely (Min/Max) | | Equally Likely (Min/Max) | ||
| Minimum<br>Maximum | | Minimum<br>Maximum | ||
| Uniformly distributed values ranging from minimum to maximum. Note that the maximum value will always be < maximum by either 1/32768 or 1/4billion, depending on the random generator selected in the model Engine options. | | Uniformly distributed values ranging from minimum to maximum. Note that the maximum value will always be < maximum by either 1/32768 or 1/4billion, depending on the random generator selected in the model Engine options. | ||
|- | |- | ||
| Triangular | | Triangular | ||
| Minimum<br>Mode<br>Maximum | | Minimum<br>Mode<br>Maximum | ||
| Distribution shaped like a triangle with its peak at mode and probabilities decreasing to zero at Minimum and Maximum, keeping the value constrained. | | Distribution shaped like a triangle with its peak at mode and probabilities decreasing to zero at Minimum and Maximum, keeping the value constrained. | ||
|- | |- | ||
| Bell Curve | | Bell Curve | ||
| Mean<br>StdDev | | Mean<br>StdDev | ||
| Normally distributed values with a distribution that looks like a bell. The standard deviation value determines the amount of variability. 95% of all values drawn will be within 3 standard deviations from the mean. | | Normally distributed values with a distribution that looks like a bell. The standard deviation value determines the amount of variability. 95% of all values drawn will be within 3 standard deviations from the mean. | ||
|- | |- | ||
| Log Normal | | Log Normal | ||
| Mu<br>Sigma | | Mu<br>Sigma | ||
| | | This is a distribution where the logarithm of the random values is normally distributed. It is used in cases where many random factors multiply together, including finance and communications.<br> | ||
|- | |- | ||
| Random Delays | | Random Delays | ||
| Mean | | Mean | ||
| | | This is the Negative Exponential or Poisson distribution and characterises the number of events that will occur over a period of time if the probability of each event is random and independent. It features a long tail of decreasing probability of occurance.<br> | ||
|- | |- | ||
| Erlang | | Erlang | ||
| Mean<br>K | | Mean<br>K | ||
| | | This characterises the time between independent events (eg: arrivals). It is actually the sum of 'K' random delays.<br> | ||
|- | |- | ||
| Weibull | | Weibull | ||
| Minimum<br>Scale<br>Shape | | Minimum<br>Scale<br>Shape | ||
| | | This distribution has a minimum and is often used to characterise equipment breakdowns. <br> | ||
|- | |- | ||
| C.D.F. Table | | C.D.F. Table | ||
| Table | | Table | ||
| | | This uses a table enabling any distribution of values to be generated. The reference must point to a "accumulating probability" column in a table where the first row cell is 0 and subsequent rows increase until the final row which must have a 1.0.<br>PL uses a uniform (0..1) draw and locates the row where that probability lies. The value in column 1 is then returned. If the value was between rows, interpolation is used.<br>This results in a continuous distribution of values. <br> | ||
|- | |- | ||
| Point Freq. Table | | Point Freq. Table | ||
| Table | | Table | ||
| | | This uses a table to define discrete values and their probabilities. The table reference points to a column of probabilities. The sum of all the probabilities in this column must be 1. A uniform (0..1) draw is made and the row (bin) within which that draw lies is found in the table. The corresponding value in column 1 is returned. There is no interpolation.<br>This results in discrete values, corresponding to the values in column 1 of the table, occuring at probabilities as set in the probability column. | ||
|} | |} | ||
<br>The Truncation / Rounding button selects either round (to closest integer) or truncate (remove fraction) operation. For times, more options appear enabling truncating/rounding a time (always in seconds) to the nearest second (1, same as unit but included for clarity), minute (60), hour (3600) or day (86400). | |||
For example: | |||
Round Unit 3.7 = 4<br>Truncate Unit 3.7 = 3<br>Round Hour 3500 = 3600 (would display as 1:00 00 in a time formatted view)<br>Truncate Hour 7100 = 3600 (1:00 00) | |||
<br> | |||
<br> | |||
<br> | Preview Button<br> Generates a graphical view of the values which would be generated using the current parameters. In cases where non numeric references are used, a preview cannot be generated. You can code your model to log the values in a table and process them to generate a graph.<br> | ||
Random Streams<br> Distributions draw upon a specific generator of basic random numbers and you are able to alter the stream number setting. Normally all random values (including ones Planimate uses internally eg: for probability switches) draw from stream 0.<br> | |||
---- | ---- | ||
[[Category:Context_Help]] | |||
[[Category: | [[Category:Data]] |
Latest revision as of 17:11, 29 June 2010
The Distribution Pattern Dialog enables values and times with random variation to be generated. For example the time a Multi-server takes to handle an item, or the inter-arrival time of items produced at an Entry.
Distributions are listed on the left. Fields appear depending on the distribution selected.
All distributions also include a truncation/rounding option button and a final scaling factor. Truncation/rounding is applied first, then scaling on the resulting number.
Truncation/rounding is useful where specific values are needed, for example when using a distribution to select between options.
Scaling is useful where the distribution might not change but needs to be adapted in continuous or batch processing situations.
Fixed Value | Value | No variation, returns a single value. |
Equally Likely | Mean Range */- |
Uniformly distributed values centred on the mean. |
Equally Likely (Min/Max) | Minimum Maximum |
Uniformly distributed values ranging from minimum to maximum. Note that the maximum value will always be < maximum by either 1/32768 or 1/4billion, depending on the random generator selected in the model Engine options. |
Triangular | Minimum Mode Maximum |
Distribution shaped like a triangle with its peak at mode and probabilities decreasing to zero at Minimum and Maximum, keeping the value constrained. |
Bell Curve | Mean StdDev |
Normally distributed values with a distribution that looks like a bell. The standard deviation value determines the amount of variability. 95% of all values drawn will be within 3 standard deviations from the mean. |
Log Normal | Mu Sigma |
This is a distribution where the logarithm of the random values is normally distributed. It is used in cases where many random factors multiply together, including finance and communications. |
Random Delays | Mean | This is the Negative Exponential or Poisson distribution and characterises the number of events that will occur over a period of time if the probability of each event is random and independent. It features a long tail of decreasing probability of occurance. |
Erlang | Mean K |
This characterises the time between independent events (eg: arrivals). It is actually the sum of 'K' random delays. |
Weibull | Minimum Scale Shape |
This distribution has a minimum and is often used to characterise equipment breakdowns. |
C.D.F. Table | Table | This uses a table enabling any distribution of values to be generated. The reference must point to a "accumulating probability" column in a table where the first row cell is 0 and subsequent rows increase until the final row which must have a 1.0. PL uses a uniform (0..1) draw and locates the row where that probability lies. The value in column 1 is then returned. If the value was between rows, interpolation is used. This results in a continuous distribution of values. |
Point Freq. Table | Table | This uses a table to define discrete values and their probabilities. The table reference points to a column of probabilities. The sum of all the probabilities in this column must be 1. A uniform (0..1) draw is made and the row (bin) within which that draw lies is found in the table. The corresponding value in column 1 is returned. There is no interpolation. This results in discrete values, corresponding to the values in column 1 of the table, occuring at probabilities as set in the probability column. |
The Truncation / Rounding button selects either round (to closest integer) or truncate (remove fraction) operation. For times, more options appear enabling truncating/rounding a time (always in seconds) to the nearest second (1, same as unit but included for clarity), minute (60), hour (3600) or day (86400).
For example:
Round Unit 3.7 = 4
Truncate Unit 3.7 = 3
Round Hour 3500 = 3600 (would display as 1:00 00 in a time formatted view)
Truncate Hour 7100 = 3600 (1:00 00)
Preview Button
Generates a graphical view of the values which would be generated using the current parameters. In cases where non numeric references are used, a preview cannot be generated. You can code your model to log the values in a table and process them to generate a graph.
Random Streams
Distributions draw upon a specific generator of basic random numbers and you are able to alter the stream number setting. Normally all random values (including ones Planimate uses internally eg: for probability switches) draw from stream 0.