Difference between revisions of "Manuals/calci/WEIBULL"

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<div style="font-size:30px">'''WEIBULL(x,alpha,beta,lv)'''</div><br/>
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<div style="font-size:30px">'''WEIBULL (Number,Alpha,Beta,Cumulative) '''</div><br/>
*<math>x </math>  is the value of the function.
+
*<math>Number </math>  is the value of the function.
*<math>alpha </math> and <math> beta </math> are the parameter of the distribution.
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*<math>Alpha </math> and <math> Beta </math> are the parameter of the distribution.
*<math>lv</math>is the logical value.
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*<math>Cumulative</math> is the logical value.
 +
**WEIBULL(),returns the Weibull distribution.
  
 
==Description==
 
==Description==
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*It is used to model the lifetime of technical devices and is used to describe the particle size distribution of particles generated by grinding, milling and crushing operations.  
 
*It is used to model the lifetime of technical devices and is used to describe the particle size distribution of particles generated by grinding, milling and crushing operations.  
 
*This distribution is closely related to the lognormal distribution.  
 
*This distribution is closely related to the lognormal distribution.  
*In <math>WEIBULL(x,alpha,beta,lv)</math>,<math> x </math> is the  value to evaluate the function.
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*In <math>WEIBULL(Number,Alpha,Beta,Cumulative)</math>,<math> Number </math> is the  value to evaluate the function.
*<math> alpha </math> is the shape parameter of the distribution.<math> beta </math> is the scale parameter of the distribution.
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*<math> Alpha </math> is the shape parameter of the distribution.<math> Beta </math> is the scale parameter of the distribution.
*<math>lv</math> is the logical value which determines the form of the distribution.  
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*<math>Cumulative</math> is the logical value which determines the form of the distribution.  
*When <math>lv</math> is TRUE, this function gives the value of the cumulative distribution. When <math>lv</math> is FALSE, then this function gives the value of the probability density function.  
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*When <math>Cumulative</math> is TRUE, this function gives the value of the cumulative distribution. When <math>Cumulative</math> is FALSE, then this function gives the value of the probability density function.  
*When we are not omitting the value of <math>lv</math>, then it consider as FALSE.  
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*When we are not omitting the value of <math>Cumulative</math>, then it consider as FALSE.  
 
*Weibull distribution is of two type :3-parameter weibull distribution and 2-parameter weibull distribution.  
 
*Weibull distribution is of two type :3-parameter weibull distribution and 2-parameter weibull distribution.  
 
*This function gives the value of 2-parameter weibull distribution by setting the third parameter (location parameter) is zero.
 
*This function gives the value of 2-parameter weibull distribution by setting the third parameter (location parameter) is zero.
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*If alpha=1, then the failure rate of the device is constant over time.  
 
*If alpha=1, then the failure rate of the device is constant over time.  
 
*If alpha>1, then the failure rate of the device increases over time.  
 
*If alpha>1, then the failure rate of the device increases over time.  
*The equation for cumulative distribution function is: <math>F(x,\alpha,\beta) = 1-e^-{(\frac{x}{β})}^α</math>
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*The equation for cumulative distribution function is: <math>F(x,\alpha,\beta)</math> =<math>1-e^-{(\frac{x}{\beta})}^\alpha</math>.
 
*The equation for probability density function is:
 
*The equation for probability density function is:
 
<math>f(x,\alpha,\beta) = \frac{\alpha}{\beta^\alpha}.x^{\alpha-1}.e^-{(\frac{x}{\beta})}^\alpha.</math>
 
<math>f(x,\alpha,\beta) = \frac{\alpha}{\beta^\alpha}.x^{\alpha-1}.e^-{(\frac{x}{\beta})}^\alpha.</math>
*When alpha =1, then this function gives the exponentail with <math>\lambda=\frac{1}{\beta}</math>.
+
*When alpha =1, then this function gives the exponential with <math>\lambda=\frac{1}{\beta}</math>.
 
*This function gives the result as error when
 
*This function gives the result as error when
 
     1. Any one of the argument is non-numeric.
 
     1. Any one of the argument is non-numeric.
     2. x is negative.
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     2. Number is negative.
     3.alpha<math>\le 0</math> or beta <math>\le 0.
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     3. Alpha<math>\le 0</math> or Beta <math>\le 0</math>
  
WEIBULL(x,alpha,beta,lv), where  , and  , and  .
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==Examples==
 +
#=WEIBULL(202,60,81,TRUE) = 1
 +
#=WEIBULL(202,60,81,FALSE) = 0
 +
#=WEIBULL(160,80,170,TRUE) = 0.00779805060
 +
#=WEIBULL(160,80,170,FALSE) = 0.0038837823333
 +
#= WEIBULL(10.5,2.1,5.3,TRUE) = 0.9850433821261
 +
#=WEIBULL(10.5,2.1,5.3,FALSE) = 0.0125713406729
  
<div id="6SpaceContent" class="zcontent" align="left">
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==Related Videos==
  
<font color="#484848"><font face="Arial, sans-serif"><font size="2">'''WEIBULL'''</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">(</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">'''x '''</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">,</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">'''a'''</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">, </font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">'''b'''</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">, </font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">'''cum'''</font></font></font><font color="#484848"><font face="Arial, sans-serif"><font size="2">)</font></font></font>
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{{#ev:youtube|mMo0Nvqq3qA|280|center|Weibull Probability}}
  
<font color="#484848"><font face="Arial, sans-serif"><font size="2">Where 'x' Is the value at which to estimate the function, 'a'(Alpha) and 'b'(Beta) are the parameters to the distribution, and 'cum' determines the form of the function.</font></font></font>
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==See Also==
 +
*[[Manuals/calci/EXPONDIST | EXPONDIST ]]
 +
*[[Manuals/calci/LOGNORMDIST  | LOGNORMDIST ]]
  
</div>
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==References==
----
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*[http://en.wikipedia.org/wiki/Weibull_distribution Weibull distribution]
<div id="1SpaceContent" class="zcontent" align="left">  <font color="#484848"><font face="Arial, sans-serif"><font size="2">This function returns the Weibull distribution. </font></font></font></div>
 
----
 
<div id="7SpaceContent" class="zcontent" align="left"> 
 
  
* <font color="#484848"><font face="Arial, sans-serif"><font size="2">WEIBULL returns the error value, when x, a, b is nonnumeric or x &lt; 0</font></font></font>
 
* <font color="#484848"><font face="Arial, sans-serif"><font size="2">WEIBULL returns the error value, when a ≤ 0 or b ≤ 0. </font></font></font>
 
* <font color="#484848"><font face="Arial, sans-serif"><font size="2">The equation for the Weibull cumulative distribution function is: </font></font></font>
 
  
<font color="#484848" face="Arial"></font>
 
  
<font color="#484848"></font>
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*[[Z_API_Functions | List of Main Z Functions]]
  
* <font color="#484848"><font face="Arial, sans-serif"><font size="2">The equation for the Weibull probability density function is: </font></font></font>
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*[[ Z3 |   Z3 home ]]
 
 
<font color="#484848"></font>
 
 
 
* <font color="#484848"><font face="Arial, sans-serif"><font size="2">When alpha = 1, WEIBULL returns the exponential distribution with: </font></font></font>
 
 
 
</div>
 
----
 
<div id="12SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="left">
 
 
 
WEIBULL
 
 
 
</div></div>
 
----
 
<div id="8SpaceContent" class="zcontent" align="left"><font color="#484848"><font face="Arial, sans-serif"><font size="2">Lets see an example,</font></font></font>
 
 
 
<font color="#484848"><font face="Arial, sans-serif"><font size="2">B</font></font></font>
 
 
 
<font color="#484848"><font face="Arial, sans-serif"><font size="2">100</font></font></font>
 
 
 
<font color="#484848"><font face="Arial, sans-serif"><font size="2">25</font></font></font>
 
 
 
<font color="#484848"><font face="Arial, sans-serif"><font size="2">110</font></font></font>
 
 
 
<font color="#484848"><font face="Arial, sans-serif"><font size="2">UNIQ686c29c343f4309c-nowiki-00000004-QINU</font></font></font>
 
 
 
<font color="#484848"><font face="Arial, sans-serif"><font size="2">UNIQ686c29c343f4309c-nowiki-00000005-QINU</font></font></font>
 
 
 
</div>
 
----
 
<div id="10SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Syntax </div><div class="ZEditBox"><center></center></div></div>
 
----
 
<div id="4SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Remarks </div></div>
 
----
 
<div id="3SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Examples </div></div>
 
----
 
<div id="11SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Description </div></div>
 
----
 
<div id="2SpaceContent" class="zcontent" align="left">
 
 
 
{| id="TABLE3" class="SpreadSheet blue"
 
|- class="even"
 
| class="    " |
 
| Column1
 
| class="  " | Column2
 
| class="  " | Column3
 
| class="  " | Column4
 
|- class="odd"
 
| class=" " | Row1
 
| class=" " | 100
 
| class="sshl_f" | 0.088165
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| class="  " | Row2
 
| class=" " | 25
 
| class="sshl_f" | 0.02104
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="odd"
 
| Row3
 
| class=" " | 110
 
| class="SelectTD" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| Row4
 
| class="sshl_f" |
 
| class="sshl_f  " |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="odd"
 
| class=" " | Row5
 
| class="sshl_f  " |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|- class="even"
 
| Row6
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|}
 
 
 
<div align="left">[[Image:calci1.gif]]</div></div>
 
----
 
<div id="9SpaceContent" class="zcontent" align="left"><div>[[Image:25.JPG|100%px|http://store.zcubes.com/33975CA25A304262905E768B19753F5D/Uploaded/25.JPG]]</div></div>
 
----
 
<div id="13SpaceContent" class="zcontent" align="left"><div>[[Image:26.JPG|100%px|http://store.zcubes.com/33975CA25A304262905E768B19753F5D/Uploaded/26.JPG]]</div></div>
 
----
 
<div id="14SpaceContent" class="zcontent" align="left"><div>[[Image:27.JPG|100%px|http://store.zcubes.com/33975CA25A304262905E768B19753F5D/Uploaded/27.JPG]]</div></div>
 
----
 

Latest revision as of 17:32, 10 August 2018

WEIBULL (Number,Alpha,Beta,Cumulative)


  • is the value of the function.
  • and are the parameter of the distribution.
  • is the logical value.
    • WEIBULL(),returns the Weibull distribution.

Description

  • This function gives the value of the weibull distribution with 2-parameters.
  • It is a continuous probability distribution.
  • Weibull distribution also called Rosin Rammler distribution.
  • It is used to model the lifetime of technical devices and is used to describe the particle size distribution of particles generated by grinding, milling and crushing operations.
  • This distribution is closely related to the lognormal distribution.
  • In , is the value to evaluate the function.
  • is the shape parameter of the distribution. is the scale parameter of the distribution.
  • is the logical value which determines the form of the distribution.
  • When is TRUE, this function gives the value of the cumulative distribution. When is FALSE, then this function gives the value of the probability density function.
  • When we are not omitting the value of , then it consider as FALSE.
  • Weibull distribution is of two type :3-parameter weibull distribution and 2-parameter weibull distribution.
  • This function gives the value of 2-parameter weibull distribution by setting the third parameter (location parameter) is zero.
  • Also if alpha<1,then the failure rate of the device decreases over time.
  • If alpha=1, then the failure rate of the device is constant over time.
  • If alpha>1, then the failure rate of the device increases over time.
  • The equation for cumulative distribution function is: =.
  • The equation for probability density function is:

  • When alpha =1, then this function gives the exponential with .
  • This function gives the result as error when
   1. Any one of the argument is non-numeric.
   2. Number is negative.
   3. Alpha or Beta 

Examples

  1. =WEIBULL(202,60,81,TRUE) = 1
  2. =WEIBULL(202,60,81,FALSE) = 0
  3. =WEIBULL(160,80,170,TRUE) = 0.00779805060
  4. =WEIBULL(160,80,170,FALSE) = 0.0038837823333
  5. = WEIBULL(10.5,2.1,5.3,TRUE) = 0.9850433821261
  6. =WEIBULL(10.5,2.1,5.3,FALSE) = 0.0125713406729

Related Videos

Weibull Probability

See Also

References