Polynomial evaluation
y = polyval(p,x)
[y,delta] = polyval(p,x,S)
y = polyval(p,x,[],mu)
[y,delta]
= polyval(p,x,S,mu)
y = polyval(p,x)
returns
the value of a polynomial of degree n
evaluated
at x
. The input argument p
is
a vector of length n+1
whose elements are the coefficients
in descending powers of the polynomial to be evaluated.
y = p1xn + p2xn–1 + … + pnx + pn+1
x
can be a matrix or a vector. In either
case, polyval
evaluates p
at
each element of x
.
[y,delta] = polyval(p,x,S)
uses
the optional output structure S
generated by polyfit
to
generate error estimates delta
. delta
is
an estimate of the standard deviation of the error in predicting
a future observation at x
by p(x)
.
If the coefficients in p
are least squares estimates
computed by polyfit
, and the errors in the data
input to polyfit
are independent, normal, and have
constant variance, then y
±delta
contains
at least 50% of the predictions of future observations at x
.
y = polyval(p,x,[],mu)
or [y,delta]
= polyval(p,x,S,mu)
use in
place of x
. In this equation, and . The centering and scaling parameters mu
= [μ1,μ2]
are optional output computed by polyfit
.
The polynomial is evaluated at x = 5, 7, and 9 with
p = [3 2 1]; polyval(p,[5 7 9])
which results in
ans = 86 162 262
For another example, see polyfit
.