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fixed typos 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@608876 13f79535-47bb-0310-9956-ffa450edef68
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Luc Maisonobe 2008-01-04 14:54:53 +00:00
parent 05bb73146d
commit 9ebcbd6b6d
1 changed files with 6 additions and 6 deletions
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12
xdocs/userguide/analysis.xml
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@ -31,7 +31,7 @@
implementations for real-valued functions of one real variable.
</p>
<p>
Possible future additions may include numerical differentation,
Possible future additions may include numerical differentiation,
integration and optimization.
</p>
</subsection>
@ -129,7 +129,7 @@ double c = solver.solve(1.0, 5.0);</source>
</p>
<p>
The <code>SecantSolver</code> uses a variant of the well known secant
algorithm. It may be a bit faster than the Brent solver for a class
algorithm. It may be a bit faster than the Brent solver for a class
of well-behaved functions.
</p>
<p>
@ -160,7 +160,7 @@ double c = solver.solve(1.0, 5.0);</source>
The Absolute Accuracy is (estimated) maximal difference between
the computed root and the true root of the function. This is
what most people think of as "accuracy" intuitively. The default
value is choosen as a sane value for most real world problems,
value is chosen as a sane value for most real world problems,
for roots in the range from -100 to +100. For accurate
computation of roots near zero, in the range form -0.0001 to
+0.0001, the value may be decreased. For computing roots
@ -182,7 +182,7 @@ double c = solver.solve(1.0, 5.0);</source>
absolute values of the numbers. This accuracy measurement is
better suited for numerical calculations with computers, due to
the way floating point numbers are represented. The default
value is choosen so that algorithms will get a result even for
value is chosen so that algorithms will get a result even for
roots with large absolute values, even while it may be
impossible to reach the given absolute accuracy.
</td>
@ -250,10 +250,10 @@ double x=0.5;
double y=function.evaluate(x);
System.out println("f("+x+")="+y);</source>
<p>
A natural cubic spline is a function consisting of a polynominal of
A natural cubic spline is a function consisting of a polynomial of
third degree for each subinterval determined by the x-coordinates of the
interpolated points. A function interpolating <code>N</code>
value pairs consists of <code>N-1</code> polynominals. The function
value pairs consists of <code>N-1</code> polynomials. The function
is continuous, smooth and can be differentiated twice. The second
derivative is continuous but not smooth. The x values passed to the
interpolator must be ordered in ascending order. It is not valid to