ebirdst_ppms_ts | R Documentation |
Calculate a time series of predictive performance metrics (PPMs) for the eBird Status and Trends model. For each week or month of the year, PPMs will be summarized independently to produce a time series. For further details on eBird Status and Trends PPMs consult the help for ebirdst_ppms.
ebirdst_ppms_ts(path, ext, summarize_by = c("weeks", "months"), ...) ## S3 method for class 'ebirdst_ppms_ts' plot(x, type = c("binary", "occurrence", "abundance"), metric = "kappa", ...)
path |
character; directory that the Status and Trends data for a given
species was downloaded to. This path is returned by |
ext |
ebirdst_extent object (optional); the spatial extent over which to calculate the PPMs. Note that ebirdst_extent objects typically specify both a spatial and temporal extent, however, within this function only the spatial component of the extent is used. |
summarize_by |
character; periods over which to summarize PPMs. PPMs can either be calculated for eBird Status and Trends weeks (as defined in ebirdst_weeks) or for the months of the year. |
... |
ignored. |
x |
ebirdst_ppms_ts object; PPMs summarized by weeks or months as
calculated by |
type |
character; the PPM type to plot, either a binary, occurrence, or abundance PPM can be plotted. |
metric |
character; the specific metric to plot, the list list of possible metrics varies by PPM type:
|
An ebirdst_pppms_ts
object containing a list of three data frames:
binary_ppms
, occ_ppms
, and abd_ppms
. Each row of these data frames
corresponds to the PPMs from one Monte Carlo iteration for a given time
period. Columns correspond to the different PPMs. binary_ppms
contains
binary or range-based PPMs, occ_ppms
contains within-range occurrence
probability PPMs, and abd_ppms
contains within-range abundance PPMs. In
some cases, PPMs may be missing, either because there isn't a large enough
test set within the spatiotemporal extent or because average occurrence or
abundance is too low. In these cases, try increasing the size of the
ebirdst_extent object. plot()
can be called on the returned
ebirdst_pppms_ts
object to plot a time series of a single PPM.
## Not run: # download example data path <- ebirdst_download("example_data", tifs_only = FALSE) # or get the path if you already have the data downloaded path <- get_species_path("example_data") # define a spatial extent to calculate ppms over e <- ebirdst_extent(c(xmin = -90, xmax = -82, ymin = 41, ymax = 48)) # compute predictive performance metrics, summarized by months ppms <- ebirdst_ppms_ts(path = path, ext = e, summarize_by = "months") # plot time series # binary, kappa plot(ppms, type = "binary", metric = "kappa") # occurrence, sensitivity plot(ppms, type = "occurrence", metric = "sensitivity") #' # abundance, poisson deviance plot(ppms, type = "abundance", metric = "poisson_dev_abd") ## End(Not run)
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