normpdf - Normal probability density function
Syntax
Y = normpdf(X,mu,sigma)
Description
Y = normpdf(X,mu,sigma) computes
the pdf at each of the values in X using the normal
distribution with mean mu and standard deviation sigma. X, mu,
and sigma can be vectors, matrices, or multidimensional
arrays that all have the same size. A scalar input is expanded to
a constant array with the same dimensions as the other inputs. The
parameters in sigma must be positive.
The normal pdf is
The likelihood function is the pdf viewed
as a function of the parameters. Maximum likelihood estimators (MLEs)
are the values of the parameters that maximize the likelihood function
for a fixed value of x.
The standard normal distribution has µ
= 0 and σ = 1.
If x is standard normal, then xσ
+ µ is also normal with mean µ and standard deviation σ.
Conversely, if y is normal with mean µ and
standard deviation σ, then x =
(y-µ) / σ
is standard normal.
Examples
mu = [0:0.1:2];
[y i] = max(normpdf(1.5,mu,1));
MLE = mu(i)
MLE =
1.5000
See Also
pdf, normcdf, norminv, normstat, normfit, normlike, normrnd
Normal Distribution
 | normlike | | normplot |  |
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