truncate

Truncate probability distribution object

Syntax

t = truncate(pd,lower,upper)

Description

t = truncate(pd,lower,upper) returns a probability distribution t, which is the probability distribution pd truncated to the specified interval with lower limit, lower, and upper limit, upper.

Examples

Truncate a Probability Distribution

Create a standard normal probability distribution object.

pd = makedist('Normal')

pd = 
  NormalDistribution

  Normal distribution
       mu = 0
    sigma = 1

Truncate the distribution to have a lower limit of -2 and an upper limit of 2.

t = truncate(pd,-2,2)

t = 
  NormalDistribution

  Normal distribution
       mu = 0
    sigma = 1
  Truncated to the interval [-2, 2]

Plot the pdf of the original and truncated distributions for a visual comparison.

x = linspace(-3,3,1000);
figure
plot(x,pdf(pd,x))
hold on
plot(x,pdf(t,x),'LineStyle','--')
legend('Normal','Truncated')
hold off

Generate Random Numbers from a Truncated Distribution

Create a standard normal probability distribution object.

pd = makedist('Normal')

pd = 
  NormalDistribution

  Normal distribution
       mu = 0
    sigma = 1

Truncate the distribution by restricting it to positive values. Set the lower limit to 0 and the upper limit to infinity.

t = truncate(pd,0,inf)

t = 
  NormalDistribution

  Normal distribution
       mu = 0
    sigma = 1
  Truncated to the interval [0, Inf]

Generate random numbers from the truncated distribution and visualize with a histogram.

r = random(t,10000,1);
histogram(r,100)

Input Arguments

pd — Probability distribution

probability distribution object

Probability distribution, specified as one of the probability distribution objects in the following table.

Distribution Object	Function or App Used to Create Probability Distribution Object
BetaDistribution	makedist, fitdist, Distribution Fitter
BinomialDistribution	makedist, fitdist, Distribution Fitter
BirnbaumSaundersDistribution	makedist, fitdist, Distribution Fitter
BurrDistribution	makedist, fitdist, Distribution Fitter
EmpiricalDistribution	fitdist
ExponentialDistribution	makedist, fitdist, Distribution Fitter
ExtremeValueDistribution	makedist, fitdist, Distribution Fitter
GammaDistribution	makedist, fitdist, Distribution Fitter
GeneralizedExtremeValueDistribution	makedist, fitdist, Distribution Fitter
GeneralizedParetoDistribution	makedist, fitdist, Distribution Fitter
HalfNormalDistribution	makedist, fitdist, Distribution Fitter
InverseGaussianDistribution	makedist, fitdist, Distribution Fitter
KernelDistribution	fitdist, Distribution Fitter
LogisticDistribution	makedist, fitdist, Distribution Fitter
LoglogisticDistribution	makedist, fitdist, Distribution Fitter
LognormalDistribution	makedist, fitdist, Distribution Fitter
LoguniformDistribution	makedist
MultinomialDistribution	makedist
NakagamiDistribution	makedist, fitdist, Distribution Fitter
NegativeBinomialDistribution	makedist, fitdist, Distribution Fitter
NormalDistribution	makedist, fitdist, Distribution Fitter
PearsonDistribution	makedist
PiecewiseLinearDistribution	makedist
PoissonDistribution	makedist, fitdist, Distribution Fitter
RayleighDistribution	makedist, fitdist, Distribution Fitter
RicianDistribution	makedist, fitdist, Distribution Fitter
StableDistribution	makedist, fitdist, Distribution Fitter
tLocationScaleDistribution	makedist, fitdist, Distribution Fitter
TriangularDistribution	makedist
UniformDistribution	makedist
WeibullDistribution	makedist, fitdist, Distribution Fitter

lower — Lower truncation limit

scalar value

Lower truncation limit, specified as a scalar value.

Data Types: single | double

upper — Upper truncation limit

scalar value

Upper truncation limit, specified as a scalar value.

Data Types: single | double

Output Arguments

t — Truncated distribution

probability distribution object

Truncated distribution, returned as a probability distribution object. The probability distribution function (pdf) of t is 0 outside the truncation interval. Inside the truncation interval, the pdf of t is equal to the pdf of pd, but divided by the probability assigned to that interval by pd.

The object properties of t are the same as those of pd with these exceptions:

• The Truncation property of t stores the truncation interval.

• The IsTruncated property of t is 1.

• The InputData property of t is empty. For a fitted distribution object, the InputData property stores the data used for distribution fitting. The truncated distribution object does not store the input data.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• The input argument pd can be a fitted probability distribution object for beta, exponential, extreme value, lognormal, normal, and Weibull distributions. Create pd by fitting a probability distribution to sample data from the fitdist function. For an example, see Code Generation for Probability Distribution Objects.

• A truncated probability distribution object cannot be an input argument of an entry-point function. To evaluate a truncated distribution using object functions such as cdf, pdf, mean, and so on, call truncate and one or more of these object functions within a single entry-point function.

For more information on code generation, see Introduction to Code Generation and General Code Generation Workflow.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Version History

Introduced in R2013a