Unifdf: Difference between revisions

From Eigenvector Research Documentation Wiki
Jump to navigation Jump to search
imported>Jeremy
(Importing text file)
imported>Jeremy
No edit summary
Line 1: Line 1:
===Purpose===
===Purpose===


Line 24: Line 23:
* '''x''' = matrix in which the sample data is stored, in the interval (-inf,inf).  
* '''x''' = matrix in which the sample data is stored, in the interval (-inf,inf).  


*  '''for''' function=quantile - matrix with values in the interval (0,1).
:: for function=quantile - matrix with values in the interval (0,1).
 
:: for function=random - vector indicating the size of the random matrix to create.
*  '''for''' function=random - vector indicating the size of the random matrix to create.


* '''a''' = "min" parameter (real).
* '''a''' = "min" parameter (real).
Line 39: Line 37:


====Cumulative:====
====Cumulative:====
 
<pre>
>> prob = unifdf('c',1.5,1,2)
>> prob = unifdf('c',1.5,1,2)
prob =
prob =
     0.5000
     0.5000
>> x    = [0:0.1:10];
>> x    = [0:0.1:10];
>> plot(x,unifdf('c',x,1,2),'b-',x,unifdf('c',x,3,7),'r-')
>> plot(x,unifdf('c',x,1,2),'b-',x,unifdf('c',x,3,7),'r-')
 
</pre>
====Density:====
====Density:====
 
<pre>
>> prob = unifdf('d',1.5,1,2)
>> prob = unifdf('d',1.5,1,2)
prob =
prob =
     1.0000
     1.0000
>> x    = [0:0.01:10];
>> x    = [0:0.01:10];
>> plot(x,unifdf('d',x,1,3),'b-',x,unifdf('d',x,1,4),'r-')
>> plot(x,unifdf('d',x,1,3),'b-',x,unifdf('d',x,1,4),'r-')
>> ylim([0 1])
>> ylim([0 1])
 
</pre>
====Quantile:====
====Quantile:====
 
<pre>
>> prob = unifdf('q',0.5,1,2)
>> prob = unifdf('q',0.5,1,2)
prob =
prob =
     1.5
     1.5
 
</pre>
====Random:====
====Random:====
 
<pre>
>> prob = unifdf('r',[4 1],2,1)
>> prob = unifdf('r',[4 1],2,1)
ans =
ans =
     1.9218
     1.9218
     1.7382
     1.7382
     1.1763
     1.1763
     1.4057
     1.4057
 
</pre>
===See Also===
===See Also===


[[betadr]], [[cauchydf]], [[chidf]], [[expdf]], [[gammadf]], [[gumbeldf]], [[laplacedf]], [[logisdf]], [[lognormdf]], [[normdf]], [[paretodf]], [[raydf]], [[triangledf]], [[weibulldf]]
[[betadf]], [[cauchydf]], [[chidf]], [[expdf]], [[gammadf]], [[gumbeldf]], [[laplacedf]], [[logisdf]], [[lognormdf]], [[normdf]], [[paretodf]], [[raydf]], [[triangledf]], [[weibulldf]]

Revision as of 13:26, 9 October 2008

Purpose

Uniform distribution.

Synopsis

prob = unifdf(function,x,a,b)

Description

Estimates cumulative distribution function (cumulative, cdf), probability density function (density, pdf), quantile (inverse of cdf), or random numbers for a Uniform distribution.

This distribution is used when all possible outcomes of an experiment are equally likely. The distribution is flat with no peak.



Inputs

  • function = [ {'cumulative'} | 'density' | 'quantile' | 'random' ], defines the functionality to be used. Note that the function recognizes the first letter of each string so that the string could be: [ 'c' | 'd' | 'q' | 'r' ].
  • x = matrix in which the sample data is stored, in the interval (-inf,inf).
for function=quantile - matrix with values in the interval (0,1).
for function=random - vector indicating the size of the random matrix to create.
  • a = "min" parameter (real).
  • b = "max" parameter (real and >= min).

Note: If inputs (x, a, and b) are not equal in size, the function will attempt to resize all inputs to the largest input using the RESIZE function.

Note: Functions will typically allow input values outside of the acceptable range to be passed but such values will return NaN in the results.

Examples

Cumulative:

>> prob = unifdf('c',1.5,1,2)
prob =
    0.5000
>> x    = [0:0.1:10];
>> plot(x,unifdf('c',x,1,2),'b-',x,unifdf('c',x,3,7),'r-')

Density:

>> prob = unifdf('d',1.5,1,2)
prob =
    1.0000
>> x    = [0:0.01:10];
>> plot(x,unifdf('d',x,1,3),'b-',x,unifdf('d',x,1,4),'r-')
>> ylim([0 1])

Quantile:

>> prob = unifdf('q',0.5,1,2)
prob =
    1.5

Random:

>> prob = unifdf('r',[4 1],2,1)
ans =
    1.9218
    1.7382
    1.1763
    1.4057

See Also

betadf, cauchydf, chidf, expdf, gammadf, gumbeldf, laplacedf, logisdf, lognormdf, normdf, paretodf, raydf, triangledf, weibulldf