docs

DESCRIPTION

 Package: TimeFRAME
 Title: Bayesian Data Analysis of Isotopic Measurement Time Series
-Version: 0.0.0.9001
+Version: 0.0.0.9002
 Authors@R: 
-    person("Philipp", "Fischer", , "fischphi@student.ethz.ch", role = c("aut", "cre"))
+    c(
+	person("Philipp", "Fischer", , "philipp.fischer@alumni.ethz.ch", role = c("aut", "cre")),
+	person("Eliza", "Harris", , "eliza.harris@sdsc.ethz.ch", role = c("ctb"))
+)
 Description: TimeFRAME is a data analysis package that can be used for Bayesian estimation of source contributions and fractionation of isotopic measurement time series. It uses Bayesian parameter estimation with Stan to estimate uncertainty and produce posterior samples. Additionally, the package provides utility functions to simulate measurements and isotopic signature data for the study of nitrous oxide.
 License: GPL (>= 3)
 Encoding: UTF-8

README.md

 # TimeFRAME
 > R package for the analysis of isotopic time series data using Bayesian hierarchical models implemented in Stan.
+> This package was created by Philipp Fischer during his ETHZ MSc thesis. See original package at: https://github.com/PhilFischer/TimeFRAME
 
 ## Installation
 Make sure R is updated and install TimeFRAME using the R console. On Windows [RTools](https://cran.r-project.org/bin/windows/Rtools/) will additionally be required.
 ```
 if (!require("devtools")) install.packages("devtools") 
-devtools::install_github("PhilFischer/TimeFRAME", build_vignettes = TRUE)
+devtools::install_github("elizaharris/TimeFRAME", build_vignettes = TRUE)
 ```
 
 TimeFRAME uses Stan as sampling library in the background. If there are any issues regarding this, please refer to the [RStan Documentation](https://mc-stan.org/users/interfaces/rstan).
 
 If you do not need additional documentation of the package provided as vignettes you can omit building them for faster installation times.
 ```
-devtools::install_github("PhilFischer/TimeFRAME", build_vignettes = FALSE)
+devtools::install_github("elizaharris/TimeFRAME", build_vignettes = FALSE)
 ```
 
 ## Usage
@@ -57,6 +58,12 @@ fit.hdgp <- fit_dgp(model, df, t = t, rho = 0.2, rho.r = 0.5, estim.rho = TRUE)
 
 ![appl_est_th](https://github.com/PhilFischer/TimeFRAME/assets/36499405/9b94e9af-80b4-44c4-80d2-d8a5dcc75e78)
 
+## Examples
+
+Download the full TimeFRAME repository or just the relevant example folder from https://gitlab.renkulab.io/eliza.harris/timeframe.
+
+You will find three folders containing example datasets and scripts as described in the TimeFRAME manuscript: gen-e_example, boma_application, incubation_application. Working through these examples will help you get started with TimeFRAME.
+
 ## References
 
 Original FRAME Model

boma_application/RunBoma_TimeFRAME.R

 
+# This script illustrates use of the TimeFRAME package to analyse the boma dataset
+
+# If you've not yet installed TimeFRAME, first run:
+# devtools::install_github("elizaharris/TimeFRAME", build_vignettes = TRUE)
+
 rm(list = ls())
 require(lubridate)
 library(TimeFRAME)

gen-e_example/RunGenE_TimeFRAME.R

@@ -4,6 +4,9 @@
 # The models are run using default values, the TimeFRAME documentation describes in detail 
 # the parameters that can be changed and edited.
 
+# If you've not yet installed TimeFRAME, first run:
+# devtools::install_github("elizaharris/TimeFRAME", build_vignettes = TRUE)
+
 rm(list = ls())
 require(lubridate)
 library(TimeFRAME)

incubation_application/RunDominikaData_TimeFRAME.R → incubation_application/RunIncubationData_TimeFRAME.R

 
+# This script illustrates use of the TimeFRAME package to analyse the soil incubation dataset
+
+# If you've not yet installed TimeFRAME, first run:
+# devtools::install_github("elizaharris/TimeFRAME", build_vignettes = TRUE)
+
 rm(list = ls())
 require(lubridate)
 library(TimeFRAME)