mean
Mean of probability distribution
Syntax
Description
Examples
Mean of Fitted Distribution
Load the sample data. Create a vector containing the first column of students’ exam grade data.
load examgrades
x = grades(:,1);
Create a normal distribution object by fitting it to the data.
pd = fitdist(x,'Normal')
pd = NormalDistribution Normal distribution mu = 75.0083 [73.4321, 76.5846] sigma = 8.7202 [7.7391, 9.98843]
The distribution object display includes the parameter estimates for the mean (mu
) and standard deviation (sigma
), and the 95% confidence intervals for the parameters.
Compute the mean of the fitted distribution.
m = mean(pd)
m = 75.0083
The mean of the normal distribution is equal to the parameter mu
.
Mean of Skewed Distribution
Create a Weibull probability distribution object.
pd = makedist('Weibull','A',5,'B',2)
pd = WeibullDistribution Weibull distribution A = 5 B = 2
Compute the mean of the distribution.
mean = mean(pd)
mean = 4.4311
Mean of a Uniform Distribution
Create a uniform distribution object.
pd = makedist('Uniform','lower',-3,'upper',5)
pd = UniformDistribution Uniform distribution Lower = -3 Upper = 5
Compute the mean of the distribution.
m = mean(pd)
m = 1
Mean of a Kernel Distribution
Load the sample data. Create a probability distribution object by fitting a kernel distribution to the miles per gallon (MPG
) data.
load carsmall; pd = fitdist(MPG,'Kernel')
pd = KernelDistribution Kernel = normal Bandwidth = 4.11428 Support = unbounded
Compute the mean of the distribution.
mean(pd)
ans = 23.7181
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 |
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 |
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 |
Output Arguments
m
— Mean
scalar value
Mean of the probability distribution, returned as a scalar value.
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. Createpd
by fitting a probability distribution to sample data from thefitdist
function. For an example, see Code Generation for Probability Distribution Objects.
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
See Also
median
| std
| makedist
| fitdist
| Distribution Fitter
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