[m,v] = unifstat(a,b)
returns the element-wise mean and variance of the continuous uniform distribution defined by
the lower endpoint (minimum) a and upper endpoint (maximum)
b. The endpoints a and b
can be scalars, vectors, or multidimensional arrays.
Compute the mean and variance of a continuous uniform standard distribution.
a = 0;
b = 1;
[m,v] = unifstat(a,b)
m =
0.5000
v =
0.0833
Create two vectors a and b, where a is the lower endpoint and b is the upper endpoint of a continuous uniform distribution. Return the mean m and variance v of the continuous uniform distribution defined by a and b.
a = 1:6;
b = 2*a;
[m,v] = unifstat(a,b)
m = 1×6
1.5000 3.0000 4.5000 6.0000 7.5000 9.0000
v = 1×6
0.0833 0.3333 0.7500 1.3333 2.0833 3.0000
If the lower endpoint a is greater than or equal to the upper endpoint b, unifstat returns NaN.
Lower endpoint of the continuous uniform distribution, specified as a numeric
scalar, vector, or array.
If a is a numeric vector or an
array, then it must have the same size as b. If
a is a numeric scalar, the function expands a
to a constant matrix that has the same dimensions as b.
Example: [0 -1 7 9]
Data Types: single | double
Upper endpoint of the continuous uniform distribution, specified as a numeric
scalar, vector, or array.
If b is a numeric vector or an
array, then it must have the same size as a. If
b is a numeric scalar, the function expands b
to a constant matrix that has the same dimensions as a.
Element-wise mean of a continuous uniform distribution, returned as a numeric
scalar, vector, or array.
Each element in m is the mean of a distribution specified by
the corresponding elements in a and b. If
a and b are not the same size,
m is the size of a and
b after any necessary scalar expansion. If
a(i) is greater than or equal to b(i), then
m(i) is NaN, where i is
the index of an element. The mean of the continuous uniform distribution with endpoints
a and b is (a + b)/2.
Element-wise variance of a continuous uniform distribution, returned as a numeric
scalar, numeric vector, or numeric array.
Each element in v is the variance of a distribution specified
by the corresponding elements in a and b. If
a and b are not the same size,
v is the size of a and
b after any necessary scalar expansion. If
a(i) is greater than or equal to b(i), then
v(i) is NaN, where i is
the index of an element. The variance of the continuous uniform distribution with
endpoints a and b is (a –
b)2/12.
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