Recent changes to Distributions

Marco Wolf — Thu, 02 Jun 2011 12:30:12 -0000

--- v4 
+++ v5 
@@ -8,154 +8,166 @@
 Normal/Gauss distribution
 ---
 Example:
-~~~~
-
+
+~~~~
+
   
     0
     1
   
 
 ~~~~
 Result:
 [[img src=expgauss.jpg width=70%]]
 
 Rectangular distribution
 ---
 Example:
+
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 [[img src=exprect.jpg width=70%]]
 
 Triangular distribution
 ---
 Example:
+
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 [[img src=exptri.jpg width=70%]]
 
 Trapezoidal distribution
 ---
-Example (new since version 0.6.3):
+Example:
+
 ~~~~
 
   
     4
     8
     2
   
 
 ~~~~
 Result:
 [[img src=trapez.jpg width=70%]]
 
 ___Warning:___
 
 Earlier versions of __MUSE__ up to version 0.6.2 used an inverse beta for definition in tag__ __. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
+
 ~~~~
 
   
     4
     8
     1
   
 
 ~~~~
 Result:
 [[img src=expcltrapez.jpg width=70%]]
 
 Arcsine distribution
 ---
 Example:
+
 ~~~~
 
   
     4
     8
   
 
 ~~~~
 Result:
 [[img src=exparcsine.jpg width=70%]]
 
 Exponential distribution
 ---
 Example:
+
 ~~~~
 
   
     
   
 
 ~~~~
 Gamma distribution
 ---
 Example:
+
 ~~~~
 
   
     
     
   
 
 ~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
+
 ~~~~
 
   
     
     
     
   
 
 ~~~~
 Example 2: Providing data
+
 ~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
 ~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
+
 ~~~~
 
   
     
   
 
 ~~~~
 Density distribution: Presampled values
 ---
 You might get to the problem, that you need a distribution that is not yet supported by  __MUSE__. We have a very rich solution for that. __MUSE__ is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
+
 ~~~~

Marco Wolf — Thu, 02 Jun 2011 12:27:41 -0000

--- v4 
+++ v5 
@@ -8,154 +8,166 @@
 Normal/Gauss distribution
 ---
 Example:
-~~~~
-
+
+~~~~
+
   
     0
     1
   
 
 ~~~~
 Result:
 [[img src=expgauss.jpg width=70%]]
 
 Rectangular distribution
 ---
 Example:
+
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 [[img src=exprect.jpg width=70%]]
 
 Triangular distribution
 ---
 Example:
+
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 [[img src=exptri.jpg width=70%]]
 
 Trapezoidal distribution
 ---
-Example (new since version 0.6.3):
+Example:
+
 ~~~~
 
   
     4
     8
     2
   
 
 ~~~~
 Result:
 [[img src=trapez.jpg width=70%]]
 
 ___Warning:___
 
 Earlier versions of __MUSE__ up to version 0.6.2 used an inverse beta for definition in tag__ __. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
+
 ~~~~
 
   
     4
     8
     1
   
 
 ~~~~
 Result:
 [[img src=expcltrapez.jpg width=70%]]
 
 Arcsine distribution
 ---
 Example:
+
 ~~~~
 
   
     4
     8
   
 
 ~~~~
 Result:
 [[img src=exparcsine.jpg width=70%]]
 
 Exponential distribution
 ---
 Example:
+
 ~~~~
 
   
     
   
 
 ~~~~
 Gamma distribution
 ---
 Example:
+
 ~~~~
 
   
     
     
   
 
 ~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
+
 ~~~~
 
   
     
     
     
   
 
 ~~~~
 Example 2: Providing data
+
 ~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
 ~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
+
 ~~~~
 
   
     
   
 
 ~~~~
 Density distribution: Presampled values
 ---
 You might get to the problem, that you need a distribution that is not yet supported by  __MUSE__. We have a very rich solution for that. __MUSE__ is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
+
 ~~~~

--- v3 
+++ v4 
@@ -8,185 +8,167 @@
 Normal/Gauss distribution
 ---
 Example:
-
-~~~~
-
+~~~~
+
   
     0
     1
   
 
 ~~~~
 Result:
-
 [[img src=expgauss.jpg width=70%]]
 
 Rectangular distribution
 ---
 Example:
-
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
-
 [[img src=exprect.jpg width=70%]]
 
 Triangular distribution
 ---
 Example:
-
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
-
 [[img src=exptri.jpg width=70%]]
 
 Trapezoidal distribution
 ---
 Example (new since version 0.6.3):
-
 ~~~~
 
   
     4
     8
     2
   
 
 ~~~~
 Result:
-
 [[img src=trapez.jpg width=70%]]
 
 ___Warning:___
 
 Earlier versions of __MUSE__ up to version 0.6.2 used an inverse beta for definition in tag__ __. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
-
 ~~~~
 
   
     4
     8
     1
   
 
 ~~~~
 Result:
-
 [[img src=expcltrapez.jpg width=70%]]
 
 Arcsine distribution
 ---
 Example:
-
 ~~~~
 
   
     4
     8
   
 
 ~~~~
 Result:
-
 [[img src=exparcsine.jpg width=70%]]
 
 Exponential distribution
 ---
 Example:
-
 ~~~~
 
   
     
   
 
 ~~~~
 Gamma distribution
 ---
 Example:
-
 ~~~~
 
   
     
     
   
 
 ~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
-
 ~~~~
 
   
     
     
     
   
 
 ~~~~
 Example 2: Providing data
-
 ~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
 ~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
-
 ~~~~
 
   
     
   
 
 ~~~~
 Density distribution: Presampled values
 ---
 You might get to the problem, that you need a distribution that is not yet supported by  __MUSE__. We have a very rich solution for that. __MUSE__ is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
-
 ~~~~
 
    
      path/density.bin
    
 
 ~~~~
 The distribution will use the given file to get random numbers. It starts with the number on position of __startvalue__ or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By __filetype__ the format of the file is specified. At the moment we support this formats:
 
- * __plain text__: Output file of __MUSE__ without additional parameters
- * __binary__: Output file of __MUSE__ with parameter __-b__
- * __linesep__: Each value is separated by a line break
- * __openBugs__: Output file of Bugs-software
+* __plain text__: Output file of __MUSE__ without additional parameters
+* __binary__: Output file of __MUSE__ with parameter __-b__
+* __linesep__: Each value is separated by a line break
+* __openBugs__: Output file of Bugs-software
 
 The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file.

Marco Wolf — Thu, 02 Jun 2011 12:26:46 -0000

--- v3 
+++ v4 
@@ -8,185 +8,167 @@
 Normal/Gauss distribution
 ---
 Example:
-
-~~~~
-
+~~~~
+
   
     0
     1
   
 
 ~~~~
 Result:
-
 [[img src=expgauss.jpg width=70%]]
 
 Rectangular distribution
 ---
 Example:
-
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
-
 [[img src=exprect.jpg width=70%]]
 
 Triangular distribution
 ---
 Example:
-
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
-
 [[img src=exptri.jpg width=70%]]
 
 Trapezoidal distribution
 ---
 Example (new since version 0.6.3):
-
 ~~~~
 
   
     4
     8
     2
   
 
 ~~~~
 Result:
-
 [[img src=trapez.jpg width=70%]]
 
 ___Warning:___
 
 Earlier versions of __MUSE__ up to version 0.6.2 used an inverse beta for definition in tag__ __. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
-
 ~~~~
 
   
     4
     8
     1
   
 
 ~~~~
 Result:
-
 [[img src=expcltrapez.jpg width=70%]]
 
 Arcsine distribution
 ---
 Example:
-
 ~~~~
 
   
     4
     8
   
 
 ~~~~
 Result:
-
 [[img src=exparcsine.jpg width=70%]]
 
 Exponential distribution
 ---
 Example:
-
 ~~~~
 
   
     
   
 
 ~~~~
 Gamma distribution
 ---
 Example:
-
 ~~~~
 
   
     
     
   
 
 ~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
-
 ~~~~
 
   
     
     
     
   
 
 ~~~~
 Example 2: Providing data
-
 ~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
 ~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
-
 ~~~~
 
   
     
   
 
 ~~~~
 Density distribution: Presampled values
 ---
 You might get to the problem, that you need a distribution that is not yet supported by  __MUSE__. We have a very rich solution for that. __MUSE__ is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
-
 ~~~~
 
    
      path/density.bin
    
 
 ~~~~
 The distribution will use the given file to get random numbers. It starts with the number on position of __startvalue__ or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By __filetype__ the format of the file is specified. At the moment we support this formats:
 
- * __plain text__: Output file of __MUSE__ without additional parameters
- * __binary__: Output file of __MUSE__ with parameter __-b__
- * __linesep__: Each value is separated by a line break
- * __openBugs__: Output file of Bugs-software
+* __plain text__: Output file of __MUSE__ without additional parameters
+* __binary__: Output file of __MUSE__ with parameter __-b__
+* __linesep__: Each value is separated by a line break
+* __openBugs__: Output file of Bugs-software
 
 The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file.

--- v2 
+++ v3 
@@ -19,174 +19,174 @@
 ~~~~
 Result:
 
-{{attachment:expgauss.jpg}}
-
+[[img src=expgauss.jpg width=70%]]
+
 Rectangular distribution
 ---
 Example:
 
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 
-{{attachment:exprect.jpg}}
+[[img src=exprect.jpg width=70%]]
 
 Triangular distribution
 ---
 Example:
 
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 
-{{attachment:exptri.jpg}}
+[[img src=exptri.jpg width=70%]]
 
 Trapezoidal distribution
 ---
 Example (new since version 0.6.3):
 
 ~~~~
 
   
     4
     8
     2
   
 
 ~~~~
 Result:
 
-{{attachment:trapez.jpg}}
-
-'''Warning:'''
-
-Earlier versions of ''MUSE'' up to version 0.6.2 used an inverse beta for definition in tag'' ''. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
+[[img src=trapez.jpg width=70%]]
+
+___Warning:___
+
+Earlier versions of __MUSE__ up to version 0.6.2 used an inverse beta for definition in tag__ __. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
 
 ~~~~
 
   
     4
     8
     1
   
 
 ~~~~
 Result:
 
-{{attachment:expcltrapez.jpg}}
+[[img src=expcltrapez.jpg width=70%]]
 
 Arcsine distribution
 ---
 Example:
 
 ~~~~
 
   
     4
     8
   
 
 ~~~~
 Result:
 
-{{attachment:exparcsine.jpg}}
+[[img src=exparcsine.jpg width=70%]]
 
 Exponential distribution
 ---
 Example:
 
 ~~~~
 
   
     
   
 
 ~~~~
 Gamma distribution
 ---
 Example:
 
 ~~~~
 
   
     
     
   
 
 ~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
 
 ~~~~
 
   
     
     
     
   
 
 ~~~~
 Example 2: Providing data
 
 ~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
 ~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
 
 ~~~~
 
   
     
   
 
 ~~~~
 Density distribution: Presampled values
 ---
-You might get to the problem, that you need a distribution that is not yet supported by  ''MUSE''. We have a very rich solution for that. ''MUSE'' is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
+You might get to the problem, that you need a distribution that is not yet supported by  __MUSE__. We have a very rich solution for that. __MUSE__ is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
 
 ~~~~
 
    
      path/density.bin
    
 
 ~~~~
-The distribution will use the given file to get random numbers. It starts with the number on position of ''startvalue'' or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By ''filetype'' the format of the file is specified. At the moment we support this formats:
-
- * ''plain text'': Output file of ''MUSE'' without additional parameters
- * ''binary'': Output file of ''MUSE'' with parameter ''-b''
- * ''linesep'': Each value is separated by a line break
- * ''openBugs'': Output file of Bugs-software
+The distribution will use the given file to get random numbers. It starts with the number on position of __startvalue__ or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By __filetype__ the format of the file is specified. At the moment we support this formats:
+
+ * __plain text__: Output file of __MUSE__ without additional parameters
+ * __binary__: Output file of __MUSE__ with parameter __-b__
+ * __linesep__: Each value is separated by a line break
+ * __openBugs__: Output file of Bugs-software
 
 The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file.

Marco Wolf — Thu, 02 Jun 2011 12:24:51 -0000

--- v2 
+++ v3 
@@ -19,174 +19,174 @@
 ~~~~
 Result:
 
-{{attachment:expgauss.jpg}}
-
+[[img src=expgauss.jpg width=70%]]
+
 Rectangular distribution
 ---
 Example:
 
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 
-{{attachment:exprect.jpg}}
+[[img src=exprect.jpg width=70%]]
 
 Triangular distribution
 ---
 Example:
 
 ~~~~
 
   
     0
     0.5
   
 
 ~~~~
 Result:
 
-{{attachment:exptri.jpg}}
+[[img src=exptri.jpg width=70%]]
 
 Trapezoidal distribution
 ---
 Example (new since version 0.6.3):
 
 ~~~~
 
   
     4
     8
     2
   
 
 ~~~~
 Result:
 
-{{attachment:trapez.jpg}}
-
-'''Warning:'''
-
-Earlier versions of ''MUSE'' up to version 0.6.2 used an inverse beta for definition in tag'' ''. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
+[[img src=trapez.jpg width=70%]]
+
+___Warning:___
+
+Earlier versions of __MUSE__ up to version 0.6.2 used an inverse beta for definition in tag__ __. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
 
 ~~~~
 
   
     4
     8
     1
   
 
 ~~~~
 Result:
 
-{{attachment:expcltrapez.jpg}}
+[[img src=expcltrapez.jpg width=70%]]
 
 Arcsine distribution
 ---
 Example:
 
 ~~~~
 
   
     4
     8
   
 
 ~~~~
 Result:
 
-{{attachment:exparcsine.jpg}}
+[[img src=exparcsine.jpg width=70%]]
 
 Exponential distribution
 ---
 Example:
 
 ~~~~
 
   
     
   
 
 ~~~~
 Gamma distribution
 ---
 Example:
 
 ~~~~
 
   
     
     
   
 
 ~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
 
 ~~~~
 
   
     
     
     
   
 
 ~~~~
 Example 2: Providing data
 
 ~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
 ~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
 
 ~~~~
 
   
     
   
 
 ~~~~
 Density distribution: Presampled values
 ---
-You might get to the problem, that you need a distribution that is not yet supported by  ''MUSE''. We have a very rich solution for that. ''MUSE'' is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
+You might get to the problem, that you need a distribution that is not yet supported by  __MUSE__. We have a very rich solution for that. __MUSE__ is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
 
 ~~~~
 
    
      path/density.bin
    
 
 ~~~~
-The distribution will use the given file to get random numbers. It starts with the number on position of ''startvalue'' or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By ''filetype'' the format of the file is specified. At the moment we support this formats:
-
- * ''plain text'': Output file of ''MUSE'' without additional parameters
- * ''binary'': Output file of ''MUSE'' with parameter ''-b''
- * ''linesep'': Each value is separated by a line break
- * ''openBugs'': Output file of Bugs-software
+The distribution will use the given file to get random numbers. It starts with the number on position of __startvalue__ or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By __filetype__ the format of the file is specified. At the moment we support this formats:
+
+ * __plain text__: Output file of __MUSE__ without additional parameters
+ * __binary__: Output file of __MUSE__ with parameter __-b__
+ * __linesep__: Each value is separated by a line break
+ * __openBugs__: Output file of Bugs-software
 
 The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file.

--- v1 
+++ v2 
@@ -9,190 +9,190 @@
 ---
 Example:
 
-~~~
-
+~~~~
+
   
     0
     1
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:expgauss.jpg}}
 
 Rectangular distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     0
     0.5
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:exprect.jpg}}
 
 Triangular distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     0
     0.5
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:exptri.jpg}}
 
 Trapezoidal distribution
 ---
 Example (new since version 0.6.3):
 
-~~~
+~~~~
 
   
     4
     8
     2
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:trapez.jpg}}
 
 '''Warning:'''
 
 Earlier versions of ''MUSE'' up to version 0.6.2 used an inverse beta for definition in tag'' ''. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     4
     8
     1
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:expcltrapez.jpg}}
 
 Arcsine distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     4
     8
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:exparcsine.jpg}}
 
 Exponential distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     
   
 
-~~~
+~~~~
 Gamma distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     
     
   
 
-~~~
+~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
 
-~~~
+~~~~
 
   
     
     
     
   
 
-~~~
+~~~~
 Example 2: Providing data
 
-~~~
+~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
-~~~
+~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
 
-~~~
+~~~~
 
   
     
   
 
-~~~
+~~~~
 Density distribution: Presampled values
 ---
 You might get to the problem, that you need a distribution that is not yet supported by  ''MUSE''. We have a very rich solution for that. ''MUSE'' is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
 
-~~~
+~~~~
 
    
      path/density.bin
    
 
-~~~
+~~~~
 The distribution will use the given file to get random numbers. It starts with the number on position of ''startvalue'' or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By ''filetype'' the format of the file is specified. At the moment we support this formats:
 
  * ''plain text'': Output file of ''MUSE'' without additional parameters
  * ''binary'': Output file of ''MUSE'' with parameter ''-b''
  * ''linesep'': Each value is separated by a line break
  * ''openBugs'': Output file of Bugs-software
 
 The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file.
 
 Complex distribution
 ---
-You can find a detailed description of this distribution [[Complex_valued_quantities|here]].
+You can find a detailed description of this distribution [Complex valued quantities](here).
 
 Correlated normal distribution
 ---

Marco Wolf — Thu, 02 Jun 2011 12:18:14 -0000

--- v1 
+++ v2 
@@ -9,190 +9,190 @@
 ---
 Example:
 
-~~~
-
+~~~~
+
   
     0
     1
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:expgauss.jpg}}
 
 Rectangular distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     0
     0.5
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:exprect.jpg}}
 
 Triangular distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     0
     0.5
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:exptri.jpg}}
 
 Trapezoidal distribution
 ---
 Example (new since version 0.6.3):
 
-~~~
+~~~~
 
   
     4
     8
     2
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:trapez.jpg}}
 
 '''Warning:'''
 
 Earlier versions of ''MUSE'' up to version 0.6.2 used an inverse beta for definition in tag'' ''. To be consistent to GS1 this changes with version 0.6.3 to the definition given there.
 
 Curvelinear trapezoidal distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     4
     8
     1
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:expcltrapez.jpg}}
 
 Arcsine distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     4
     8
   
 
-~~~
+~~~~
 Result:
 
 {{attachment:exparcsine.jpg}}
 
 Exponential distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     
   
 
-~~~
+~~~~
 Gamma distribution
 ---
 Example:
 
-~~~
+~~~~
 
   
     
     
   
 
-~~~
+~~~~
 Student-t distribution
 ---
 Example 1: Precalculated values
 
-~~~
+~~~~
 
   
     
     
     
   
 
-~~~
+~~~~
 Example 2: Providing data
 
-~~~
+~~~~
 
   
     
       2.0
       3.0
       4.0
       9.0
     
   
 
-~~~
+~~~~
 Special distributions
 ===
 Constant values
 ---
 Example:
 
-~~~
+~~~~
 
   
     
   
 
-~~~
+~~~~
 Density distribution: Presampled values
 ---
 You might get to the problem, that you need a distribution that is not yet supported by  ''MUSE''. We have a very rich solution for that. ''MUSE'' is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this:
 
-~~~
+~~~~
 
    
      path/density.bin
    
 
-~~~
+~~~~
 The distribution will use the given file to get random numbers. It starts with the number on position of ''startvalue'' or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By ''filetype'' the format of the file is specified. At the moment we support this formats:
 
  * ''plain text'': Output file of ''MUSE'' without additional parameters
  * ''binary'': Output file of ''MUSE'' with parameter ''-b''
  * ''linesep'': Each value is separated by a line break
  * ''openBugs'': Output file of Bugs-software
 
 The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file.
 
 Complex distribution
 ---
-You can find a detailed description of this distribution [[Complex_valued_quantities|here]].
+You can find a detailed description of this distribution [Complex valued quantities](here).
 
 Correlated normal distribution
 ---

Standard distributions === Most of the following distributions are listed in the first GUM supplement. The algorithms how to generate random values of these distributions using numbers from a random number generator for rectangular distributed values are also listed there. Please note that most parameters in the following examples of the influences are parametrised. Normal/Gauss distribution --- Example: ~ 0 1 ~ Result: {{attachment:expgauss.jpg}} Rectangular distribution --- Example: ~ 0 0.5 ~ Result: {{attachment:exprect.jpg}} Triangular distribution --- Example: ~ 0 0.5 ~ Result: {{attachment:exptri.jpg}} Trapezoidal distribution --- Example (new since version 0.6.3): ~ 4 8 2 ~ Result: {{attachment:trapez.jpg}} '''Warning:''' Earlier versions of ''MUSE'' up to version 0.6.2 used an inverse beta for definition in tag'' ''. To be consistent to GS1 this changes with version 0.6.3 to the definition given there. Curvelinear trapezoidal distribution --- Example: ~ 4 8 1 ~ Result: {{attachment:expcltrapez.jpg}} Arcsine distribution --- Example: ~ 4 8 ~ Result: {{attachment:exparcsine.jpg}} Exponential distribution --- Example: ~ ~ Gamma distribution --- Example: ~ ~ Student-t distribution --- Example 1: Precalculated values ~ ~ Example 2: Providing data ~ 2.0 3.0 4.0 9.0 ~ Special distributions === Constant values --- Example: ~ ~ Density distribution: Presampled values --- You might get to the problem, that you need a distribution that is not yet supported by ''MUSE''. We have a very rich solution for that. ''MUSE'' is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this: ~ path/density.bin ~ The distribution will use the given file to get random numbers. It starts with the number on position of ''startvalue'' or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By ''filetype'' the format of the file is specified. At the moment we support this formats: * ''plain text'': Output file of ''MUSE'' without additional parameters * ''binary'': Output file of ''MUSE'' with parameter ''-b'' * ''linesep'': Each value is separated by a line break * ''openBugs'': Output file of Bugs-software The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file. Complex distribution --- You can find a detailed description of this distribution [[Complex_valued_quantities|here]]. Correlated normal distribution --- Related Topics === * [Cut distributions]

Marco Wolf — Thu, 02 Jun 2011 12:16:39 -0000

Standard distributions === Most of the following distributions are listed in the first GUM supplement. The algorithms how to generate random values of these distributions using numbers from a random number generator for rectangular distributed values are also listed there. Please note that most parameters in the following examples of the influences are parametrised. Normal/Gauss distribution --- Example: ~~~ 0 1 ~~~ Result: {{attachment:expgauss.jpg}} Rectangular distribution --- Example: ~~~ 0 0.5 ~~~ Result: {{attachment:exprect.jpg}} Triangular distribution --- Example: ~~~ 0 0.5 ~~~ Result: {{attachment:exptri.jpg}} Trapezoidal distribution --- Example (new since version 0.6.3): ~~~ 4 8 2 ~~~ Result: {{attachment:trapez.jpg}} '''Warning:''' Earlier versions of ''MUSE'' up to version 0.6.2 used an inverse beta for definition in tag'' ''. To be consistent to GS1 this changes with version 0.6.3 to the definition given there. Curvelinear trapezoidal distribution --- Example: ~~~ 4 8 1 ~~~ Result: {{attachment:expcltrapez.jpg}} Arcsine distribution --- Example: ~~~ 4 8 ~~~ Result: {{attachment:exparcsine.jpg}} Exponential distribution --- Example: ~~~ ~~~ Gamma distribution --- Example: ~~~ ~~~ Student-t distribution --- Example 1: Precalculated values ~~~ ~~~ Example 2: Providing data ~~~ 2.0 3.0 4.0 9.0 ~~~ Special distributions === Constant values --- Example: ~~~ ~~~ Density distribution: Presampled values --- You might get to the problem, that you need a distribution that is not yet supported by ''MUSE''. We have a very rich solution for that. ''MUSE'' is able to handle files with density definitions of distributions and interpret them as a given distribution. The file consist of a list of numbers in different formats and takes this numbers as random numbers. The definition of such a distribution looks like this: ~~~ path/density.bin ~~~ The distribution will use the given file to get random numbers. It starts with the number on position of ''startvalue'' or else on a random position. Each time when the simulation system askes for a new random number the distribution returns the next value in the file. If the distribution reaches the value on the last position, it resets the pointer to the first position and continues from there on. By ''filetype'' the format of the file is specified. At the moment we support this formats: * ''plain text'': Output file of ''MUSE'' without additional parameters * ''binary'': Output file of ''MUSE'' with parameter ''-b'' * ''linesep'': Each value is separated by a line break * ''openBugs'': Output file of Bugs-software The parameter dimension is only neccessary for \Muse files. It tells the programm which dimension or set of values to use, if there is more than one dimension stored in the data file. Complex distribution --- You can find a detailed description of this distribution [[Complex_valued_quantities|here]]. Correlated normal distribution --- Related Topics === * [Cut distributions]