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unifcdf

Continuous uniform cumulative distribution function

Description

example

p = unifcdf(x,a,b) returns the continuous uniform cumulative distribution function (cdf) at each value in x using the corresponding lower endpoint a and upper endpoint b.

example

p = unifcdf(x,a,b,"upper") returns the complement of the continuous uniform cdf using an algorithm that more accurately computes the extreme upper tail probabilities.

Examples

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Calculate the probability that an observation from the standard uniform distribution will be less than 0.75. The standard uniform distribution corresponds to a = 0 and b = 1.

p = unifcdf(0.75)
p = 0.7500

The probability of an observation being less than 0.75 is 0.75.

Calculate the probability that an observation from a uniform distribution with a = -1 and b = 1 will be less than 0.5.

p = unifcdf(0.5,-1,1)
p = 0.7500

The probability of an observation being less than 0.5 is 0.75.

Calculate the probability of an observation from the standard uniform distribution being greater than 0.75.

p = unifcdf(0.75,"upper")
p = 0.2500

The probability of an observation being greater than 0.75 is 0.25.

Input Arguments

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Values at which to evaluate the continuous uniform cdf, specified as a numeric scalar, vector, or array.

To evaluate the cdf at multiple values, specify x with an array.

If x is a vector or an array it must have the same size as a and b. If x is a scalar, the function expands x to a constant matrix that has the same dimensions as a and b.

Example: [0.5 0.75 1]

Data Types: single | double

Lower endpoint of the continuous uniform cdf, specified as a numeric scalar, vector, or array.

To evaluate the cdfs of multiple distributions specify a with an array.

If a is a vector or an array it must have the same size as x and b. If a is a scalar, the function expands a to a constant matrix that has the same dimensions as x and b.

Example: [0 -1 7 9]

Data Types: single | double

Upper endpoint of the continuous uniform cdf, specified as a numeric scalar, vector, or array.

To evaluate the cdfs of multiple distributions specify b with an array.

If b is a vector or an array it must have the same size as x and a. If b is a scalar, the function expands b to a constant matrix that has the same dimensions as x and a.

Example: [1 1 10 12]

Data Types: single | double

Output Arguments

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Cdf values evaluated at each point in x, returned as a nonnegative scalar, vector, or array with elements in the range [0,1]. The output p is the same size as x, a, and b after any necessary scalar expansion. Each element in p is the cdf value of the distribution specified by the corresponding elements in a and b, evaluated at the corresponding element in x.

The uniform cdf is

p=F(x|a,b)=xabaI[a,b](x)

Data Types: single | double

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced before R2006a