spearman_rho ()

int
spearman_rho (const int *list,
              const DATASET *dset,
              gretlopt opt,
              PRN *prn);

Calculates and prints Spearman's rank correlation coefficient for the two variables specified in the list .

spearman_rho_func ()

gretl_matrix *
spearman_rho_func (const double *x,
                   const double *y,
                   int n,
                   int *err);

kendall_tau ()

int
kendall_tau (const int *list,
             const DATASET *dset,
             gretlopt opt,
             PRN *prn);

Calculates and prints Kendall's rank correlation tau statistic for the two variables specified in list .

kendall_tau_func ()

gretl_matrix *
kendall_tau_func (const double *x,
                  const double *y,
                  int n,
                  int *err);

lockes_test ()

double
lockes_test (const double *x,
             int t1,
             int t2,
             int *err);

Performs Charles Locke's nonparametric test for whether an empirical distribution (namely, that of x over the range t1 to t2 ) is gamma. See C. Locke, "A Test for the Composite Hypothesis that a Population has a Gamma Distribution," Commun. Statis.-Theor. Meth. A5(4), 351-364 (1976). Also see Shapiro and Chen, Journal of Quality Technology 33(1), Jan 2001.

vge_gamma_test ()

double
vge_gamma_test (const double *x,
                int t1,
                int t2,
                int *err);

Performs the test described by J. A. Villaseñor and E. González-Estrada (Statistics and Probability Letters, 96 (2015) pp. 281–286) for the null hypothesis that x is gamma-distributed over the range t1 to t2 .

For the sake of compatibility with the gamma_test() function in the R package named "goft" we divide by n-1 in computing the covariance term sxz , although this is not recommended by the authors of the above- noted publication.

runs_test ()

int
runs_test (int v,
           const DATASET *dset,
           gretlopt opt,
           PRN *prn);

Performs, and prints the results of, the runs test for randomness for the variable specified by v . The normal approximation is that given in Gary Smith, Statistical Reasoning, 2e, p. 674.

diff_test ()

int
diff_test (const int *list,
           const DATASET *dset,
           gretlopt opt,
           PRN *prn);

Performs, and prints the results of, a non-parametric test for a difference between two variables or groups. The specific test performed depends on opt .

sort_pairs_by_x ()

int
sort_pairs_by_x (gretl_matrix *x,
                 gretl_matrix *y,
                 int **order,
                 char **labels);

Orders the elements of x and y by increasing value of x . Optionally, returns in order an array of integers representing the order in which the original observations appear in the sorted vectors. Also optionally sorts an accomanying array of observation labels.

loess_fit ()

gretl_matrix *
loess_fit (const gretl_matrix *x,
           const gretl_matrix *y,
           int d,
           double q,
           gretlopt opt,
           int *err);

Computes loess estimates based on William Cleveland, "Robust Locally Weighted Regression and Smoothing Scatterplots", Journal of the American Statistical Association, Vol. 74 (1979), pp. 829-836. Typically one expects that d = 1 and q is in the neighborhood of 0.5.

The x,y pairs must be pre-sorted by increasing value of x ; an error is flagged if this is not the case. See also sort_pairs_by_x().

kernel_bandwidth ()

double
kernel_bandwidth (const double *x,
                  int n);