libsim Versione 7.1.11
|
Compute the linear regression coefficients between the two random variables provided, taking into account missing data. Continua...
Compute the linear regression coefficients between the two random variables provided, taking into account missing data.
Data are considered missing when at least one variable has a missing value. The regression is computed using the method of linear least squares. The input and output parameters are either REAL or DOUBLE PRECISION.
SUBROUTINE stat_linear_regression()
sample1(:) | REAL,INTENT(in) or DOUBLE PRECISION,INTENT(in) the first variable |
sample2(:) | REAL,INTENT(in) or DOUBLE PRECISION,INTENT(in) the second variable |
alpha0 | REAL,INTENT(out) or DOUBLE PRECISION,INTENT(out) the 0-th order coefficient of the regression computed |
alpha1 | REAL,INTENT(out) or DOUBLE PRECISION,INTENT(out) the first order coefficient of the regression computed |
mask(:) | LOGICAL,OPTIONAL,INTENT(in) additional mask to be and'ed with missing values |
nomiss | LOGICAL,OPTIONAL,INTENT(in) if provided and .TRUE. it disables all the checks for missing data and empty sample and enables the use of a fast algorithm |
Definizione alla linea 107 del file simple_stat.f90.