Relative asymptotic bias [%] of x^1% from T = IG distribution, assuming F = GE model.

<p>Relative asymptotic bias [%] of <math><mrow><msub><mi>x</mi><mo>^</mo><mrow><mn>1</mn><mi>%</mi></mrow></msub></mrow></math> from T = IG distribution, assuming F = GE model.</p

The relation of conventional skewness coefficient <i>C</i>_<i>S</i> versus conventional variation coefficient <i>C</i>_<i>V</i> for two-parameter inverse Gaussian, IG, and generalized exponential, GE, distributions plotted with the Polish data of 90-year annual peak flow series.

<p>The relation of conventional skewness coefficient <i>C</i>_<i>S</i> versus conventional variation coefficient <i>C</i>_<i>V</i> for two-parameter inverse Gaussian, IG, and generalized exponential, GE, distributions plotted with the Polish data of 90-year annual peak flow series.</p

Probability of inconsistent selection [%] for competing GE and IG distributions by the <i>K</i> or <i>QK</i> discrimination procedures.

<p>Probability of inconsistent selection [%] for competing GE and IG distributions by the <i>K</i> or <i>QK</i> discrimination procedures.</p

Probability of correct selection [%] for competing GE and IG distributions by the <i>KS</i> discrimination procedure.

<p>Probability of correct selection [%] for competing GE and IG distributions by the <i>KS</i> discrimination procedure.</p

Probability density functions of GE and IG distributions for <i>μ</i> = 1.0 and selected values of <i>C</i>_<i>V</i> and thus <i>C</i>_<i>S</i>.

<p>Probability density functions of GE and IG distributions for <i>μ</i> = 1.0 and selected values of <i>C</i>_<i>V</i> and thus <i>C</i>_<i>S</i>.</p

Probability of correct selection [%] for competing GE and IG distributions by the <i>R</i>² discrimination procedures.

<p>Probability of correct selection [%] for competing GE and IG distributions by the <i>R</i>² discrimination procedures.</p

Relative asymptotic bias [%] of x^1% from T = GE distribution, assuming F = IG model.

<p>Relative asymptotic bias [%] of <math><mrow><msub><mi>x</mi><mo>^</mo><mrow><mn>1</mn><mi>%</mi></mrow></msub></mrow></math> from T = GE distribution, assuming F = IG model.</p

The relation of conventional skewness coefficient <i>C</i>_<i>S</i> versus conventional variation coefficient <i>C</i>_<i>V</i> for some two-parameter distributions commonly used if FFA plotted with the Polish data of 90-year annual peak flow series.

<p>Distributions: Ga–gamma, We–Weibull, LN–log-normal, LL–log-logistic, LG–log-Gumbel, Exp–exponential.</p

The relation of linear skewness coefficient <i>LC</i>_<i>S</i> versus linear variation coefficient <i>LC</i>_<i>V</i> for some two-parameter distributions commonly used if FFA plotted with the Polish data of 90-year annual peak flow series.

<p>Distributions: Ga–gamma, We–Weibull, LN–log-normal, LL–log-logistic, LG–log-Gumbel, Exp–exponential.</p

The relation of linear skewness coefficient <i>LC</i>_<i>S</i> versus linear variation coefficient <i>LC</i>_<i>V</i> for two-parameter inverse Gaussian, IG, and generalized exponential, GE, distributions plotted with the Polish data of 90-year annual peak flow series.

<p>The relation of linear skewness coefficient <i>LC</i>_<i>S</i> versus linear variation coefficient <i>LC</i>_<i>V</i> for two-parameter inverse Gaussian, IG, and generalized exponential, GE, distributions plotted with the Polish data of 90-year annual peak flow series.</p