View source: R/Module_calcPercChangeMCMC.R
calcPercChangeMCMC | R Documentation |
MCMC version of trend metric calculation This function calculates the percent change in abundances based on an exponential model of population decline, as per IUCN guidelines It estimates a distribution of percent declines over the period of the time-series, and provides the probability of declines being greater than a specified threhold
calcPercChangeMCMC(
vec.in,
method = "jags",
model.in = NULL,
perc.change.bm = -25,
na.skip = FALSE,
out.type = "short",
mcmc.plots = FALSE,
convergence.check = FALSE,
logged = TRUE
)
vec.in |
vector with numeric values |
method |
either "jags" (default), "rstanarm", or "rstan". For properties and discussion of strengths/limitations, refer to the MetricsCOSEWIC wiki. |
model.in |
if NULL, use the built in functions for each method: trend.bugs.1() for jags, ETC |
perc.change.bm |
benchmark for Prob(Decl>BM), default = -25 |
na.skip |
if TRUE, skip the calculations when vec.in contains any NA |
out.type |
"short" or "long". "short" gives summary table of posterior plus "PercChange" and "ProbDecl" "long" also includes the full mcmc samples and the jags output object |
mcmc.plots |
if true, create the standard series of MCMC diagnostic plots Note that these are printed to the default device (i.e. need to external wrap the function call inside a pdf /dev.off call) To get a plot of the model fit, run this function with out.type = "long", and then use plot.trend.fit(). |
convergence.check |
if TRUE, do an automated convergence check |
logged |
if TRUE, then the input is already log-transformed, and the Perc Change is calculated on the exponentiated fitted values. Default is TRUE |
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