Changeset 191

Ignore:
Timestamp:
Oct 26, 2004, 2:59:47 PM (18 years ago)
Message:

more simplistic interface

File:
1 edited

Legend:

Unmodified
 r180 /// /// @return average of x /// inline double average_x(void) const {return x_.average();} /// /// @return average of y /// inline double average_y(void) const {return y_.average();} /// /// @return sum of squared values \f$\sum x_i^2 \f$ /// inline double average_sqrx(void) const {return x_.average_sqr();} /// /// @return sum of squared values \f$\sum y_i^2 \f$ /// inline double average_sqry(void) const {return y_.average_sqr();} /// /// \f$\frac{\sum_i (x_i-m_x)(y_i-m_y)}{\sqrt{\sum_i /// (x_i-m_x)^2\sum_i (y_i-m_y)^2}}\f$ /// /// @return average \f$\frac{\sum x_i}{n} \f$ /// @return number of pair of data points /// inline double mean_x(void) const { return x_.mean(); } /// /// @return average \f$\frac{\sum y_i}{n} \f$ /// inline double mean_y(void) const { return y_.mean(); } /// /// @return @return sum of squared values \f$\sum x_i^2 \f$. /// inline double mean_sqrx(void) const { return x_.mean_sqr(); } inline long n(void) const { return x_.n(); } /// /// @return @return sum of squared values \f$\sum y_i^2 \f$. /// @return mean of xy /// inline double mean_sqry(void) const { return y_.mean_sqr(); } inline double mean_xy(void) const { return xy_/n(); } /// /// @return number of data points /// @return average squared difference between x and y \f$/// \frac{1}{N} \sum (x-y)^2 \f$ /// inline double n(void) const { return x_.n(); } inline double mse(void) { return x_.mean_sqr()+y_.mean_sqr()-2*mean_xy(); } /// /// /// The standard deviation is defined as the square root of the /// variance. @return standard deviation of x /// inline double standard_deviation_x(void) const {  return x_.std(); } /// /// The standard deviation is defined as the square root of the /// variance. @return standard deviation of y /// inline double standard_deviation_y(void) const {  return y_.std(); } /// /// The standard deviation is defined as the square root of the /// variance. @return standard deviation of x /// inline double std_x(void) const {  return x_.std(); } /// /// The standard deviation is defined as the square root of the /// variance. @return standard deviation of y /// inline double std_y(void) const {  return y_.std(); } /// /// @return standard error of x, i.e. standard deviation of the mean /// inline double standard_error_x(void) const { return x_.standard_error(); } /// /// @return standard error of y, i.e. standard deviation of the mean /// inline double standard_error_y(void) const { return y_.standard_error(); } /// /// @return the sum of x /// inline double sum_x(void) const { return x_.sum_x(); } /// /// @return the sum of y /// inline double sum_y(void) const { return y_.sum_x(); } /// /// @return the sum of x squared /// inline double sum_sqr_x(void) const { return x_.sum_xsqr(); } /// /// @return the sum of y squared /// inline double sum_sqr_y(void) const { return y_.sum_xsqr(); } /// /// @return the sum of xy /// inline double sum_xy(void) const { return xy_; } /// /// The variance is calculated using the (n-1) correction, so the /// expectation value is unbiased @return variance x /// inline double variance_x(void) const { return x_.variance(); } /// /// The variance is calculated using the (n-1) correction, so the /// expectation value is unbiased @return variance of y /// inline double variance_y(void) const { return y_.variance(); } ///