diff --git a/DESCRIPTION b/DESCRIPTION index fef240b23f5eea2478d633623393ea6d8ced8ade..cc1496993532236fa3aeb705ec48b3d647cbfdbf 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: airGR Type: Package Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling -Version: 1.0.6.9 +Version: 1.0.6.10 Date: 2017-04-05 Authors@R: c( person("Laurent", "Coron", role = c("aut", "trl")), diff --git a/man/ErrorCrit_KGE.Rd b/man/ErrorCrit_KGE.Rd index 6ce1678b53c302540d5e5123e9ed68550793c2ad..28efcc811b8f8356ca615a6ff51ee63f0da04c1b 100644 --- a/man/ErrorCrit_KGE.Rd +++ b/man/ErrorCrit_KGE.Rd @@ -41,9 +41,9 @@ the use of the function for model calibration: the product CritValue*Multiplier The KGE formula is \deqn{KGE = 1 - \sqrt(r - 1)^2 + (\alpha - 1)^2 + (\beta - 1)^2}{KGE = 1 - sqrt((r - 1)² + (\alpha - 1)² + (\beta - 1)²)} with the following sub-criteria: -\deqn{r = the linear correlation coefficient between Q_s and Q_o}{r = the linear correlation coefficient between Q[s] and Q[o]} -\deqn{\alpha = \frac{\sigma_s}{\sigma_o}}{\alpha = \sigma[s] / \sigma[o]} -\deqn{\beta = \frac{\mu_s}{\mu_o}}{\beta = \mu[s] / \mu[o]} +\deqn{r = \mathrm{the\: linear\: correlation\: coefficient\: between\:} Q_{sim}\: \mathrm{and\:} Q_{obs}}{r = the linear correlation coefficient between Q[sim] and Q[obs]} +\deqn{\alpha = \frac{\sigma_{sim}}{\sigma_{obs}}}{\alpha = \sigma[sim] / \sigma[obs]} +\deqn{\beta = \frac{\mu_{sim}}{\mu_{obs}}}{\beta = \mu[sim] / \mu[obs]} } \examples{ diff --git a/man/ErrorCrit_KGE2.Rd b/man/ErrorCrit_KGE2.Rd index 82c344ccda16f4552e9c6764f1200734365626e7..0fa1cd12481368cfb8be4e3b1f382c01840b0352 100644 --- a/man/ErrorCrit_KGE2.Rd +++ b/man/ErrorCrit_KGE2.Rd @@ -41,9 +41,9 @@ the use of the function for model calibration: the product CritValue*Multiplier The KGE' formula is \deqn{KGE' = 1 - \sqrt{(r - 1)^2 + (\gamma - 1)^2 + (\beta - 1)^2}}{KGE' = 1 - sqrt((r - 1)² + (\gamma - 1)² + (\beta - 1)²)} with the following sub-criteria: -\deqn{r = the linear correlation coefficient between Q_s and Q_o}{r = is the linear correlation coefficient between Q[s] and Q[o]} -\deqn{\alpha = \frac{CV_s}{CV_o}}{\alpha = CV[s] / CV[o]} -\deqn{\beta = \frac{\mu_s}{\mu_o}}{\beta = \mu[s] / \mu[o]} +\deqn{r = \mathrm{the\: linear\ correlation\: coefficient\: between\:} Q_{sim}\: \mathrm{and\:} Q_{obs}}{r = is the linear correlation coefficient between Q[sim] and Q[obs]} +\deqn{\gamma = \frac{CV_{sim}}{CV_{obs}}}{\gamma = CV[sim] / CV[obs]} +\deqn{\beta = \frac{\mu_{sim}}{\mu_{obs}}}{\beta = \mu[sim] / \mu[obs]} } \examples{