paleofire (version 1.1.8)

paleofire-package: paleofire: A package for the Global Charcoal Database

Description

The paleofire package provides tools to extract and analyse charcoal sedimentary data stored in the Global Charcoal Database. Main functionalities includes data extraction and sites selection, transformation and homogenization of the charcoal records as well as regional to global compositing.

Author(s)

Global Paleofire Working Group

Maintainer

Olivier Blarquez

Details

Package:

paleofire

Type:

Package

Version:

1.1.8

Date:

2015-12-21

License:

GPL (>=2)

References

Blarquez, O., Vannière, B., Marlon, J. R., Daniau, A. L., Power, M. J., Brewer, S., & Bartlein, P. J. (2014). paleofire: an R package to analyse sedimentary charcoal records from the Global Charcoal Database to reconstruct past biomass burning. Computers & Geosciences, 72, 255-261.

See Also

http://gpwg.paleofire.org

Examples

## Not run: 
# ## Interactive sites selection:
# # ID=pfInteractive()
# 
# ## Site selection using criterions
# # Boreal Eastern North American sites with at least one
# # dating point each 2500 year
# 
# ID=pfSiteSel(lat>50, lat<70, long>-90, long<(-50), date_int<=2500, l12==1)
# plot(ID,zoom="world")
# 
# ## Modify plot
# plot(ID,zoom="sites")
# 
# ## Simple test for transforming data
# # Select site 1 (Cygnet Lake)
# 
# ID1=pfSiteSel(id_site==1)
# plot(ID1)
# 
# # Transformation of data
# TR=pfTransform(ID1,method=c("MinMax", "Box-Cox", "Z-Score"))
# 
# # Plot Transformed and raw data
# # First retrieve raw data for Cygnet using pfExtract
# 
# RAW=pfExtract(ID=1)
# 
# dev.off()
# par(mfrow=(c(2,1)))
# 
# plot(RAW[,3],RAW[,4],type="l")
# plot(TR$Age,TR$TransData,type="l")
# 
# ## Transforming and Compositing
# ## Example 1: Usage as in Power et al. 2008
# ## Data transformation
# 
# TR1=pfTransform(ID, method=c("MinMax","Box-Cox","Z-Score"),BasePeriod=c(200,2000))
# 
# ## Diagnostic pdf file with transformed series:
# # pfDiagnostic(ID, method=c("MinMax","Box-Cox","Z-Score"),BasePeriod=c(200,2000), 
# # FileName = "Diagnostic.pdf")
# 
# ## Compositing: basic binning procedure
# COMP=pfComposite(TR1, binning=TRUE, bins=seq(0,8000,500))
# plot(COMP)
# 
# ## The result matrix can be saved
# # write.csv(COMP$Result,file="temp.csv")
# 
# ## Compositing: Using the locfit package equivalent procedure to Daniau et al. 2012
# 
# COMP2=pfCompositeLF(TR1, tarAge=seq(-50,8000,20), binhw=20, hw=500,nboot=100)
# plot(COMP2)
# 
# ## And save
# write.csv(COMP2$Result,file="temp2.csv")
# ## End(Not run)