Sample Correlation Coefficient
. We have generated N observations of correlated Nakagami-lognormal RVs following the methods described above.
In order to evaluate consistency and dependency of measured and simulated data, sample correlation coefficient
(r) is determined as follows:
r = Sample correlation coefficient
[C.sub.v](RMSE) = Coefficient of variation of the root-mean-square error n = Sample size Subscripts s = simulation variable m = measured variable i = index REFERENCES
where r is the sample correlation coefficient
between R and I.
A 2 x 2 variance-covariance matrix [V.sub.rec] is used to describe the complex-valued variable S in terms of its standard uncertainties u(R) and u(I) for R and I and the sample correlation coefficient
r between R and I in a rectangular coordinate,
Possibly these disparities resulted from variability of the sample correlation coefficient
for small N.
R([y.sub.1],[y.sub.2]) = the sample correlation coefficient
between variable [y.sub.1] and [y.sub.2];
1) Pearson's sample correlation coefficient
, let's denote it by [r.sub.p]
3.19 Distribution of the Sample Correlation Coefficient
From Bivariate Normal Distribution
The positive correlation between X and Y is measured by the sample correlation coefficient
David's tables of the sample correlation coefficient
: distribution function and percentiles.