Commit 2ddf9dd5 authored by unknown's avatar unknown
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v1.0.9.69 minor text revisions on vignettes

parent 690f4cd0
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.0.9.68
Date: 2017-12-05
Version: 1.0.9.69
Date: 2017-12-06
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl")),
person("Charles", "Perrin", role = c("aut", "ths")),
......
......@@ -26,7 +26,7 @@
@phdthesis{le_moine_bassin_2008,
title = {Le bassin versant de surface vu par le souterrain : une voie d’amélioration des performances et du réalisme des modèles pluie-débit ?},
url = {http://webgr.irstea.fr/wp-content/uploads/2012/07/2008-LE_MOINE-THESE.pdf},
school = {Université Pierre et Marie Curie - Paris VI},
school = {Université Pierre et Marie Curie, Paris 6},
author = {Le Moine, Nicolas},
year = {2008},
keywords = {airGR, IRSTEA-HBAN-HYDRO},
......
......@@ -16,7 +16,7 @@ library(DEoptim)
library(hydroPSO)
library(Rmalschains)
# source("airGR.R")
set.seed(123)
```
......@@ -29,7 +29,7 @@ The Michel's calibration strategy (`Calibration_Michel()` function) is the calib
We show here how to use different R packages to perform parameter estimation.
In this vignette, we use the **GR4J** model to illustrate the different optimization strategies.
In particular, we assume that the R global environment contains input climate data, observed discharge and functions from the **airGR** [Get Started](V01_get_started.html) vignette, as shown below.
In particular, we assume that the R global environment contains input climate data, observed discharge and functions from the [Get Started](V01_get_started.html) vignette, as shown below.
Please note that the calibration period is defined in the `CreateRunOptions()` function .
```{r, warning=FALSE, fig.keep='none', results='hide', fig.height=10, fig.width=10, eval=TRUE, echo=FALSE, message=FALSE}
......
......@@ -17,6 +17,7 @@ library(FME)
library(ggmcmc)
library(dplyr)
# source("airGR.R")
set.seed(123)
```
......
......@@ -63,7 +63,7 @@ summary(Param_Sets_GR4J)
## Object model preparation
We assume that the R global environment contains data and functions from the **airGR** [Get Started](V01_get_started.html) vignette.
We assume that the R global environment contains data and functions from the [Get Started](V01_get_started.html) vignette.
The calibration period has been defined from **1990-01-01** to **1990-02-28**, and the validation period from **1990-03-01** to **1999-12-31**.
......
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