Poisson probability density function
computes the Poisson probability density function at each of the values in
y = poisspdf(x,lambda)x using the rate parameters in lambda.
x and lambda can be scalars, vectors,
matrices, or multidimensional arrays that all have the same size. If only one argument is a
scalar, poisspdf expands it to a constant array with the same dimensions
as the other argument.
poisspdf is a function specific to Poisson distribution.
Statistics and Machine Learning Toolbox™ also offers the generic function pdf, which supports various probability distributions. To use
pdf, specify the probability distribution name and its parameters.
Alternatively, create a PoissonDistribution probability distribution
object and pass the object as an input argument. Note that the distribution-specific
function poisspdf is faster than the generic function
pdf.
Use the Probability Distribution Function app to create an interactive plot of the cumulative distribution function (cdf) or probability density function (pdf) for a probability distribution.