A package for the R language which generates step plots, influence plots, coefficient-distribution-influence (CDI) plots, and influence metrics for linear models as described in the paper [Bentley, N., Kendrick, T. H., Starr, P. J., & Breen, P. A. (2011). Influence plots and metrics: tools for better understanding fisheries catch-per-unit-effort standardisations. ICES Journal of Marine Science, 69: 84-88. doi:10.1093/icesjms/fsr174](https://icesjms.oxfordjournals.org/cgi/reprint/fsr174? ijkey=zZGx3RoK1zkxhaL&keytype=ref) (There is a pre-print, pre-review version here but the above link is recommended as it gives full access to the final version)

The package is still in development. A beta version is available under Releases. Eventually influ will be submitted to the Comprehensive R Archive Network for direct installation via the install.packages R function.

We recommend looking at the influ vignette first. But if you don't have time for even that, here's an even quicker run down....

#Install the package after downloading it
install.packages("/path/to/influ_0.X.zip",repos=NULL) #Windows
install.packages("/path/to/influ_0.X.tar.gz",repos=NULL) #Linux

#Load the package
library(influ)

#Fit a glm model (the first term, in this case year, should be a factor!)
myModel = glm(log(catch)~year+effort+month+area+depth+method,data=myData)
 
##Create an influence object for that model
myInfl = Influence$new(myModel)
myInfl$calc()

##Look at the summary data.frame and execute the various methods
## to create plots
myInfl$summary
myInfl$stanPlot()
myInfl$stepPlot()
myInfl$influPlot()
myInfl$cdiPlot('month')
myInfl$cdiPlotAll()

There is also a reference manual and if that fails you could always try the source code!

The initial development of this software was done by Nokome Bentley, Trophia Ltd and funded by the New Zealand Seafood Industry Council Ltd.