truncate

Truncate probability distribution object

Syntax

t = truncate(pd,lower,upper)

Description

example

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

collapse all

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

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

collapse all

Probability distribution, specified as a probability distribution object. Create a probability distribution object with specified parameter values using makedist.

Alternatively, for fittable distributions, create a probability distribution object by fitting it to data using fitdist or the Distribution Fitter app.

Lower truncation limit, specified as a scalar value.

Data Types: single | double

Upper truncation limit, specified as a scalar value.

Data Types: single | double

Output Arguments

collapse all

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.

Introduced in R2013a