Function vector_covariance (o2scl)

O2scl : Function List

template<class vec_t, class vec2_t>
double o2scl::vector_covariance(size_t n, const vec_t &data1, const vec2_t &data2, double mean1, double mean2)

Compute the covariance of two vectors.

This function computes

\[ \frac{1}{n-1} \sum_i \left(x_i - {\bar{x}}\right) \left(y_i - {\bar{y}}\right) \]

where \( {\bar{x}} \) and \( {\bar{y}} \) are specified in mean1 and mean2, respectively.

This function produces the same results as gsl_stats_covariance_m().

If n is zero, this function will return zero without calling the error handler.

template<class vec_t, class vec2_t>
double o2scl::vector_covariance(const vec_t &data1, const vec2_t &data2, double mean1, double mean2)

Compute the covariance of two vectors.

This function computes

\[ \frac{1}{n-1} \sum_i \left(x_i - {\bar{x}}\right) \left(y_i - {\bar{y}}\right) \]

where \( {\bar{x}} \) and \( {\bar{y}} \) are specified in mean1 and mean2, respectively.

This function produces the same results as gsl_stats_covariance_m().

If n is zero, this function will return zero without calling the error handler.

template<class vec_t, class vec2_t>
double o2scl::vector_covariance(size_t n, const vec_t &data1, const vec2_t &data2)

Compute the covariance of two vectors.

This function computes

\[ \frac{1}{n-1} \sum_i \left(x_i - {\bar{x}}\right) \left(y_i - {\bar{y}}\right) \]

where \( {\bar{x}} \) and \( {\bar{y}} \) are the averages of data1 and data2 and are computed automatically using vector_mean().

This function produces the same results as gsl_stats_covariance().

If n is zero, this function will return zero without calling the error handler.

template<class vec_t, class vec2_t>
double o2scl::vector_covariance(const vec_t &data1, const vec2_t &data2)

Compute the covariance of two vectors.

This function computes

\[ \frac{1}{n-1} \sum_i \left(x_i - {\bar{x}}\right) \left(y_i - {\bar{y}}\right) \]

where \( {\bar{x}} \) and \( {\bar{y}} \) are the averages of data1 and data2 and are computed automatically using vector_mean().

This function produces the same results as gsl_stats_covariance().

If n is zero, this function will return zero without calling the error handler.