This class offers functions to perform least-squares fits to a straight line model,  .  
 More...
.  
 More...
#include <OpenMS/MATH/STATISTICS/LinearRegression.h>
| Public Member Functions | |
| LinearRegression () | |
| Constructor.  More... | |
| virtual | ~LinearRegression () | 
| Destructor.  More... | |
| template<typename Iterator > | |
| void | computeRegression (double confidence_interval_P, Iterator x_begin, Iterator x_end, Iterator y_begin) | 
| This function computes the best-fit linear regression coefficients  of the model  for the dataset  .  More... | |
| template<typename Iterator > | |
| void | computeRegressionNoIntercept (double confidence_interval_P, Iterator x_begin, Iterator x_end, Iterator y_begin) | 
| This function computes the best-fit linear regression coefficient  of the model  for the dataset  .  More... | |
| template<typename Iterator > | |
| void | computeRegressionWeighted (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  of the model  for the weighted dataset  .  More... | |
| DoubleReal | getIntercept () const | 
| Non-mutable access to the y-intercept of the straight line.  More... | |
| DoubleReal | getSlope () const | 
| Non-mutable access to the slope of the straight line.  More... | |
| DoubleReal | getXIntercept () const | 
| Non-mutable access to the x-intercept of the straight line.  More... | |
| DoubleReal | getLower () const | 
| Non-mutable access to the lower border of confidence interval.  More... | |
| DoubleReal | getUpper () const | 
| Non-mutable access to the upper border of confidence interval.  More... | |
| DoubleReal | getTValue () const | 
| Non-mutable access to the value of the t-distribution.  More... | |
| DoubleReal | getRSquared () const | 
| Non-mutable access to the squared pearson coefficient.  More... | |
| DoubleReal | getStandDevRes () const | 
| Non-mutable access to the standard deviation of the residuals.  More... | |
| DoubleReal | getMeanRes () const | 
| Non-mutable access to the residual mean.  More... | |
| DoubleReal | getStandErrSlope () const | 
| Non-mutable access to the standard error of the slope.  More... | |
| DoubleReal | getChiSquared () const | 
| Non-mutable access to the chi squared value.  More... | |
| DoubleReal | getRSD () const | 
| Non-mutable access to relelative standard deviation.  More... | |
| Protected Member Functions | |
| void | computeGoodness_ (double *X, double *Y, int N, double confidence_interval_P) | 
| Computes the goodness of the fitted regression line.  More... | |
| template<typename Iterator > | |
| 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.  More... | |
| template<typename Iterator > | |
| 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.  More... | |
| Protected Attributes | |
| double | intercept_ | 
| The intercept of the fitted line with the y-axis.  More... | |
| double | slope_ | 
| The slope of the fitted line.  More... | |
| double | x_intercept_ | 
| The intercept of the fitted line with the x-axis.  More... | |
| double | lower_ | 
| The lower bound of the confidence intervall.  More... | |
| double | upper_ | 
| The upper bound of the confidence intervall.  More... | |
| double | t_star_ | 
| The value of the t-statistic.  More... | |
| double | r_squared_ | 
| The squared correlation coefficient (Pearson)  More... | |
| double | stand_dev_residuals_ | 
| The standard deviation of the residuals.  More... | |
| double | mean_residuals_ | 
| Mean of residuals.  More... | |
| double | stand_error_slope_ | 
| The standard error of the slope.  More... | |
| double | chi_squared_ | 
| The value of the Chi Squared statistic.  More... | |
| double | rsd_ | 
| the relative standard deviation  More... | |
| Private Member Functions | |
| LinearRegression (const LinearRegression &arg) | |
| Not implemented.  More... | |
| LinearRegression & | operator= (const LinearRegression &arg) | 
| Not implemented.  More... | |
This class offers functions to perform least-squares fits to a straight line model,  .
. 
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:
| 
 | inline | 
Constructor.
| 
 | inlinevirtual | 
Destructor.
| 
 | private | 
Not implemented.
Computes the goodness of the fitted regression line.
Referenced by LinearRegression::computeRegression(), LinearRegression::computeRegressionNoIntercept(), and LinearRegression::computeRegressionWeighted().
| void computeRegression | ( | double | confidence_interval_P, | 
| Iterator | x_begin, | ||
| Iterator | x_end, | ||
| Iterator | y_begin | ||
| ) | 
This function computes the best-fit linear regression coefficients  of the model
 of the model  for the dataset
 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.
 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.
| Exception::UnableToFit | is thrown if fitting cannot be performed | 
References LinearRegression::chi_squared_, LinearRegression::computeGoodness_(), LinearRegression::intercept_, LinearRegression::iteratorRange2Arrays_(), and LinearRegression::slope_.
| void computeRegressionNoIntercept | ( | double | confidence_interval_P, | 
| Iterator | x_begin, | ||
| Iterator | x_end, | ||
| Iterator | y_begin | ||
| ) | 
This function computes the best-fit linear regression coefficient  of the model
 of the model  for the dataset
 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.
 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.
| Exception::UnableToFit | is thrown if fitting cannot be performed | 
References LinearRegression::chi_squared_, LinearRegression::computeGoodness_(), LinearRegression::intercept_, LinearRegression::iteratorRange2Arrays_(), and LinearRegression::slope_.
| void computeRegressionWeighted | ( | 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  of the model
 of the model  for the weighted dataset
 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.
 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.
| Exception::UnableToFit | is thrown if fitting cannot be performed | 
References LinearRegression::chi_squared_, LinearRegression::computeGoodness_(), LinearRegression::intercept_, LinearRegression::iteratorRange3Arrays_(), and LinearRegression::slope_.
| DoubleReal getChiSquared | ( | ) | const | 
Non-mutable access to the chi squared value.
| DoubleReal getIntercept | ( | ) | const | 
Non-mutable access to the y-intercept of the straight line.
| DoubleReal getLower | ( | ) | const | 
Non-mutable access to the lower border of confidence interval.
| DoubleReal getMeanRes | ( | ) | const | 
Non-mutable access to the residual mean.
| DoubleReal getRSD | ( | ) | const | 
Non-mutable access to relelative standard deviation.
| DoubleReal getRSquared | ( | ) | const | 
Non-mutable access to the squared pearson coefficient.
| DoubleReal getSlope | ( | ) | const | 
Non-mutable access to the slope of the straight line.
| DoubleReal getStandDevRes | ( | ) | const | 
Non-mutable access to the standard deviation of the residuals.
| DoubleReal getStandErrSlope | ( | ) | const | 
Non-mutable access to the standard error of the slope.
| DoubleReal getTValue | ( | ) | const | 
Non-mutable access to the value of the t-distribution.
| DoubleReal getUpper | ( | ) | const | 
Non-mutable access to the upper border of confidence interval.
| DoubleReal getXIntercept | ( | ) | const | 
Non-mutable access to the x-intercept of the straight line.
| 
 | protected | 
Copies the distance(x_begin,x_end) elements starting at x_begin and y_begin into the arrays x_array and y_array.
Referenced by LinearRegression::computeRegression(), and LinearRegression::computeRegressionNoIntercept().
| 
 | 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.
Referenced by LinearRegression::computeRegressionWeighted().
| 
 | private | 
Not implemented.
| 
 | protected | 
The value of the Chi Squared statistic.
Referenced by LinearRegression::computeRegression(), LinearRegression::computeRegressionNoIntercept(), and LinearRegression::computeRegressionWeighted().
| 
 | protected | 
The intercept of the fitted line with the y-axis.
Referenced by LinearRegression::computeRegression(), LinearRegression::computeRegressionNoIntercept(), and LinearRegression::computeRegressionWeighted().
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 | protected | 
The lower bound of the confidence intervall.
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 | protected | 
Mean of residuals.
| 
 | protected | 
The squared correlation coefficient (Pearson)
| 
 | protected | 
the relative standard deviation
| 
 | protected | 
The slope of the fitted line.
Referenced by LinearRegression::computeRegression(), LinearRegression::computeRegressionNoIntercept(), and LinearRegression::computeRegressionWeighted().
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 | protected | 
The standard deviation of the residuals.
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 | protected | 
The standard error of the slope.
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 | protected | 
The value of the t-statistic.
| 
 | protected | 
The upper bound of the confidence intervall.
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 | protected | 
The intercept of the fitted line with the x-axis.
| OpenMS / TOPP release 1.11.1 | Documentation generated on Thu Nov 14 2013 11:19:38 using doxygen 1.8.5 |