mastif to include covariates.
name to use for a variable in the model that comes from
last data year to include.
The version of
treeData used in
mastif can have additional tree years included when there are seed trap years that were not censused or when AR(p) effects extend observations to impute the p years before and after a tree was observed. The
function mastFillCensus makes this version of
treeData available to the user. The
function mastClimate provides a quick way to add plot-year covariates to
A covariate like minimum monthly temperature is stored in a
year_month format, where
file are plot names matching
file could be
2012_1, 2012_2, ... for the 12 months in the year. The
numeric vector months holds the months to be included in the annual values, e.g.,
c(3, 4) for minimum winter temperatures during the period from March through April. To find the minimum for this period, set
More detailed vignettes can be obtained with:
numeric vector equal in length to the number of rows in
treeData that can be added as a
column and included in
James S Clark, firstname.lastname@example.org
Clark, J.S., C. Nunes, and B. Tomasek. 2019. Foodwebs based on unreliable foundations: spatio-temporal masting merged with consumer movement, storage, and diet. Ecological Monographs, e01381.
mastFillCensus to fill tree census
mastif for analysis
A more detailed vignette is can be obtained with:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
d <- "https://github.com/jimclarkatduke/mast/blob/master/liriodendronExample.rData?raw=True" repmis::source_data(d) inputs <- list( specNames = specNames, seedNames = seedNames, treeData = treeData, seedData = seedData, xytree = xytree, xytrap = xytrap) # interpolate census, add years for AR(p) model inputs <- mastFillCensus(inputs, p = 3) treeData <- inputs$treeData #now includes additional years # include minimum spring temperature of previous year cfile <- tempfile(fileext = '.csv') d <- "https://github.com/jimclarkatduke/mast/blob/master/tmin.csv?raw=True" download.file(d, destfile=cfile) tyears <- treeData$year - 1 tplots <- treeData$plot tmp <- mastClimate( file = cfile, plots = tplots, years = tyears, months = 1:4, FUN = 'min') treeData$tminSprAnomaly <- tmp$x[,3] inputs$treeData <- treeData formulaRep <- as.formula( ~ diam ) formulaFec <- as.formula( ~ diam + tminSprAnomaly ) yearEffect <- list(groups ='species', p = 3) # AR(3) model, species are lag groups output <- mastif(inputs = inputs, formulaFec, formulaRep, yearEffect = yearEffect, ng = 2000, burnin = 1000)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.