#include <OpenMS/MATH/STATISTICS/LinearRegression.h>
It capsulates the GSL methods for a weighted and an unweighted linear regression.
Next to the intercept with the y-axis and the slope of the fitted line, this class computes the:
Public Member Functions | |
LinearRegression () | |
Constructor. | |
LinearRegression (LinearRegression const &arg) | |
Copy constructor. | |
LinearRegression & | operator= (LinearRegression const &arg) |
Assignment. | |
virtual | ~LinearRegression () |
Destructor. | |
int | computeInterceptXAxis (double confidence_interval_P, Iterator x_begin, Iterator x_end, Iterator y_begin) |
This function computes the best-fit linear regression coefficients ![]() ![]() ![]() | |
int | computeInterceptXAxisWeighted (double confidence_interval_P, Iterator x_begin, Iterator x_end, Iterator y_begin, Iterator w_begin) |
This function computes the best-fit linear regression coefficients ![]() ![]() ![]() | |
DoubleReal | getIntercept () const |
Non-mutable access to the y-intercept of the straight line. | |
DoubleReal | getSlope () const |
Non-mutable access to the slope of the straight line. | |
DoubleReal | getXIntercept () const |
Non-mutable access to the x-intercept of the straight line. | |
DoubleReal | getLower () const |
Non-mutable access to the lower border of confidence interval. | |
DoubleReal | getUpper () const |
Non-mutable access to the upper border of confidence interval. | |
DoubleReal | getTValue () const |
Non-mutable access to the value of the t-distribution. | |
DoubleReal | getRSquared () const |
Non-mutable access to the squared pearson coefficient. | |
DoubleReal | getStandDevRes () const |
Non-mutable access to the standard deviation of the residuals. | |
DoubleReal | getMeanRes () const |
Non-mutable access to the residual mean. | |
DoubleReal | getStandErrSlope () const |
Non-mutable access to the standard error of the slope. | |
DoubleReal | getChiSquared () const |
Non-mutable access to the chi squared value. | |
DoubleReal | getRSD () const |
Non-mutable access to relelative standard deviation. | |
Protected Member Functions | |
void | computeGoodness_ (double *X, double *Y, int N, double confidence_interval_P) |
Computes the goodness of the fitted regression line. | |
void | iteratorRange2Arrays_ (Iterator x_begin, Iterator x_end, Iterator y_begin, double *x_array, double *y_array) |
Copies the distance(x_begin,x_end) elements starting at x_begin and y_begin into the arrays x_array and y_array. | |
void | iteratorRange3Arrays_ (Iterator x_begin, Iterator x_end, Iterator y_begin, Iterator w_begin, double *x_array, double *y_array, double *w_array) |
Copy the distance(x_begin,x_end) elements starting at x_begin, y_begin and w_begin into the arrays x_array, y_array and w_array. | |
Protected Attributes | |
double | intercept_ |
The intercept of the fitted line with the y-axis. | |
double | slope_ |
The slope of the fitted line. | |
double | x_intercept_ |
The intercept of the fitted line with the x-axis. | |
double | lower_ |
The lower bound of the confidence intervall. | |
double | upper_ |
The upper bound of the confidence intervall. | |
double | t_star_ |
The value of the t-statistic. | |
double | r_squared_ |
The squared correlation coefficient (Pearson). | |
double | stand_dev_residuals_ |
The standard deviation of the residuals. | |
double | mean_residuals_ |
Mean of residuals. | |
double | stand_error_slope_ |
The standard error of the slope. | |
double | chi_squared_ |
The value of the Chi Squared statistic. | |
double | rsd_ |
the relative standard deviation |
LinearRegression | ( | ) | [inline] |
Constructor.
LinearRegression | ( | LinearRegression< Iterator > const & | arg | ) | [inline] |
Copy constructor.
virtual ~LinearRegression | ( | ) | [inline, virtual] |
Destructor.
LinearRegression& operator= | ( | LinearRegression< Iterator > const & | arg | ) | [inline] |
Assignment.
int computeInterceptXAxis | ( | double | confidence_interval_P, | |
Iterator | x_begin, | |||
Iterator | x_end, | |||
Iterator | y_begin | |||
) | [inline] |
This function computes the best-fit linear regression coefficients of the model
for the dataset
.
The values in x-dimension of the dataset are given by the iterator range [x_begin,x_end) and the corresponding y-values start at position y_begin.
For a "x %" Confidence Interval use confidence_interval_P = x/100. For example the 95% Confidence Interval is supposed to be an interval that has a 95% chance of containing the true value of the parameter.
int computeInterceptXAxisWeighted | ( | double | confidence_interval_P, | |
Iterator | x_begin, | |||
Iterator | x_end, | |||
Iterator | y_begin, | |||
Iterator | w_begin | |||
) | [inline] |
This function computes the best-fit linear regression coefficients of the model
for the weighted dataset
.
The values in x-dimension of the dataset are given by the iterator range [x_begin,x_end) and the corresponding y-values start at position y_begin. They will be weighted by the values starting at w_begin.
For a "x %" Confidence Interval use confidence_interval_P = x/100. For example the 95% Confidence Interval is supposed to be an interval that has a 95% chance of containing the true value of the parameter.
DoubleReal getIntercept | ( | ) | const [inline] |
Non-mutable access to the y-intercept of the straight line.
DoubleReal getSlope | ( | ) | const [inline] |
Non-mutable access to the slope of the straight line.
DoubleReal getXIntercept | ( | ) | const [inline] |
Non-mutable access to the x-intercept of the straight line.
DoubleReal getLower | ( | ) | const [inline] |
Non-mutable access to the lower border of confidence interval.
DoubleReal getUpper | ( | ) | const [inline] |
Non-mutable access to the upper border of confidence interval.
DoubleReal getTValue | ( | ) | const [inline] |
Non-mutable access to the value of the t-distribution.
DoubleReal getRSquared | ( | ) | const [inline] |
Non-mutable access to the squared pearson coefficient.
DoubleReal getStandDevRes | ( | ) | const [inline] |
Non-mutable access to the standard deviation of the residuals.
DoubleReal getMeanRes | ( | ) | const [inline] |
Non-mutable access to the residual mean.
DoubleReal getStandErrSlope | ( | ) | const [inline] |
Non-mutable access to the standard error of the slope.
DoubleReal getChiSquared | ( | ) | const [inline] |
Non-mutable access to the chi squared value.
DoubleReal getRSD | ( | ) | const [inline] |
Non-mutable access to relelative standard deviation.
void computeGoodness_ | ( | double * | X, | |
double * | Y, | |||
int | N, | |||
double | confidence_interval_P | |||
) | [inline, protected] |
Computes the goodness of the fitted regression line.
void iteratorRange2Arrays_ | ( | Iterator | x_begin, | |
Iterator | x_end, | |||
Iterator | y_begin, | |||
double * | x_array, | |||
double * | y_array | |||
) | [inline, protected] |
Copies the distance(x_begin,x_end) elements starting at x_begin and y_begin into the arrays x_array and y_array.
void iteratorRange3Arrays_ | ( | Iterator | x_begin, | |
Iterator | x_end, | |||
Iterator | y_begin, | |||
Iterator | w_begin, | |||
double * | x_array, | |||
double * | y_array, | |||
double * | w_array | |||
) | [inline, protected] |
Copy the distance(x_begin,x_end) elements starting at x_begin, y_begin and w_begin into the arrays x_array, y_array and w_array.
double intercept_ [protected] |
The intercept of the fitted line with the y-axis.
double slope_ [protected] |
The slope of the fitted line.
double x_intercept_ [protected] |
The intercept of the fitted line with the x-axis.
double lower_ [protected] |
The lower bound of the confidence intervall.
double upper_ [protected] |
The upper bound of the confidence intervall.
double t_star_ [protected] |
The value of the t-statistic.
double r_squared_ [protected] |
The squared correlation coefficient (Pearson).
double stand_dev_residuals_ [protected] |
The standard deviation of the residuals.
double mean_residuals_ [protected] |
Mean of residuals.
double stand_error_slope_ [protected] |
The standard error of the slope.
double chi_squared_ [protected] |
The value of the Chi Squared statistic.
double rsd_ [protected] |
the relative standard deviation
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