Class to calculate simple (first and second moments) averages.
More...
#include <yat/statistics/Averager.h>
|
| Averager (void) |
|
| Averager (double x, double xx, long n) |
|
| Averager (const Averager &a) |
|
const Averager & | operator= (const Averager &) |
| The assignment operator.
|
|
template<class Derived > |
const Averager & | operator+= (const averager_base2< Derived > &other) |
| plus assignment operator
|
|
double | cv (void) const |
| Coeffient of variation.
|
|
double | standard_error (void) const |
|
double | std (void) const |
| The standard deviation is defined as the square root of the variance.
|
|
double | std (double m) const |
| The standard deviation is defined as the square root of the variance.
|
|
double | sum_xx (void) const |
|
double | sum_xx_centered (void) const |
|
double | variance (double m) const |
| The variance with known mean.
|
|
double | variance (void) const |
| The estimated variance.
|
|
double | variance_unbiased (void) const |
|
void | add (double x, long n=1) |
| add a data point
|
|
double | mean (void) const |
| mean
|
|
long | n (void) const |
| number of data points
|
|
void | rescale (double a) |
| Rescales the object.
|
|
void | reset (void) |
| Reset object.
|
|
double | sum_x (void) const |
|
|
class | averager_base< Averager > |
|
|
(Note that these are not member functions.)
|
template<typename InputIterator > |
void | add (Averager &a, InputIterator first, InputIterator last) |
| adding a range of values to Averager a
|
|
Class to calculate simple (first and second moments) averages.
- See Also
- AveragerWeighted AveragerPair AveragerPairWeighted
theplu::yat::statistics::Averager::Averager |
( |
void |
| ) |
|
theplu::yat::statistics::Averager::Averager |
( |
double |
x, |
|
|
double |
xx, |
|
|
long |
n |
|
) |
| |
Constructor taking sum of x, sum of squared x, xx, and number of samples n.
theplu::yat::statistics::Averager::Averager |
( |
const Averager & |
a | ) |
|
add a data point
Adding n number of data point(s) with value x.
add n data points with value x
add one data point with value delta + mean()
add a set of n data points with mean mean and centralized squaed sum cm
add one data point with value delta + mean()
Coeffient of variation.
Coeffient of variation (cv) is defined as ratio between the standard deviation and the mean: .
- Returns
- standard deviation divided by mean.
mean
- Returns
- Mean of presented data,
number of data points
- Returns
- Number of data points
plus assignment operator
Add another Averager
Rescales the object.
,
rescale as
rescales and calles rescale1(double)
Reset object.
Restore Averager as if data were never added
- Returns
- Standard error, i.e. standard deviation of the mean
The standard deviation is defined as the square root of the variance.
- Returns
- The standard deviation, root of the variance().
The standard deviation is defined as the square root of the variance.
- Returns
- Standard deviation around m, root of the variance(m).
- Returns
- The sum of data values
- Returns
- The sum of squares
- Returns
-
The variance with known mean.
The variance is calculated as .
- Returns
- Variance when the mean is known to be m.
The estimated variance.
The variance is calculated as , where is the mean.
- Returns
- Estimation of variance
sum of values squared values centralized
The documentation for this class was generated from the following file: