title | output | bibliography | csl | ||||||
---|---|---|---|---|---|---|---|---|---|
Lag Detection |
|
man/bibliography.bib |
man/apa-5th.csl |
This package fits glms over species time series to detect a stagnant growth rate (lag phase) in species populations. The code is based on @Hyndman2015-rt and has been published on www.robjhyndman.com.
You can install the lag detection package from github with:
# install.packages("devtools")
devtools::install_github("PhillRob/lag-package")
library(lag-package)
This is a basic example which shows you how to solve a common problem:
lagTest <- runlag(x = TimeSeriesNatPlantNZN,y = AnnualFrequencyNatPlantNZ)
Invasive species time series from NZ is included as test data is included from @Aikio2010-fv.
load("data/AnnualFrequencyNatPlantNZ.rda")
load("data/TimeSeriesNatPlantNZN.rda")
You can use gbifwranger.R
to wrap GBIF data downloaded using the rgbif package by @Scott_Chamberlain_Vijay_Barve_Dan_Mcglinn_Damiano_Oldoni_Laurens_Geffert_Karthik_Ram2018-zi into the format required by the lag code.
# get gbif occurences
if (!require(rgbif)) install.packages('rgbif')
library(rgbif)
species <- c("Vachellia farnesiana", "Achyranthes aspera"))
gbifkey <- sapply(species, function(x)
name_backbone(name = x, kingdom = 'plants'),
USE.NAMES = FALSE)
gbifkey <- as.data.frame(gbifkey)
gbifocc <- occ_search(taxonKey = gbifkey[1,], limit = 200000, country = "US", return = "data")
gbifocc <- ldply(gbifocc, data.frame)
# format gbif data to format for lag code
lagdata <- gbifwrangler(x = gbifocc)