Nothing
### rewritten commsimulator
"commsimulator" <-
function (x, method, thin = 1)
{
## Do not yet warn on deprecation to allow smooth transition
##.Deprecated("nullmodel", package="vegan")
method <- match.arg(method,
c("r0","r1","r2","r00","c0","swap", "tswap",
"backtrack", "quasiswap"))
if (method == "r0")
method <- "r0_old"
x <- as.matrix(x)
out <- simulate(nullmodel(x, method), nsim = 1, thin = thin)
out <- out[,,1]
attributes(out) <- attributes(x)
out
}
### density and densityplot
### density & densityplot methods for vegan functions returning
### statistics from permuted/simulated data. These are modelled after
### density.oecosimu and densityplot.oecosimu (which are in their
### separate files).
## anosim
`density.anosim` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<anosim.result>))",
package="vegan")
obs <- x$statistic
## Put observed statistic among permutations
out <- density(c(obs, x$perm), ...)
out$call <- match.call()
out$observed <- obs
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
## adonis can return a matrix of terms, hence we also have densityplot()
`density.adonis` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<adonis.result>))",
package="vegan")
cols <- ncol(x$f.perms)
if (cols > 1)
warning("'density' is meaningful only with one term, you have ", cols)
obs <- x$aov.tab$F.Model
obs <- obs[!is.na(obs)]
out <- density(c(obs, x$f.perms), ...)
out$observed <- obs
out$call <- match.call()
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
`densityplot.adonis` <-
function(x, data, xlab = "Null", ...)
{
.Deprecated("densityplot(permustats(<adonis.result>))",
package="vegan")
obs <- x$aov.tab$F.Model
obs <- obs[!is.na(obs)]
sim <- rbind(obs, x$f.perms)
nm <- rownames(x$aov.tab)[col(sim)]
densityplot( ~ as.vector(sim) | factor(nm, levels = unique(nm)),
xlab = xlab,
panel = function(x, ...) {
panel.densityplot(x, ...)
panel.abline(v = obs[panel.number()], ...)
},
...)
}
## mantel
`density.mantel` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<mantel.result>))",
package="vegan")
obs <- x$statistic
out <- density(c(obs, x$perm), ...)
out$observed <- obs
out$call <- match.call()
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
## mrpp
`density.mrpp` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<mrpp.result>))",
package="vegan")
obs <- x$delta
out <- density(c(obs, x$boot.deltas), ...)
out$observed <- obs
out$call <- match.call()
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
## anova.cca does not return permutation results, but permutest.cca
## does. However, permutest.cca always finds only one statistic. Full
## tables anova.cca are found by repeated calls to permutest.cca.
`density.permutest.cca` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<permutest.result>))",
package="vegan")
obs <- x$F.0
out <- density(c(obs, x$F.perm), ...)
out$observed <- obs
out$call <- match.call()
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
## protest
`density.protest` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<protest.result>))",
package="vegan")
obs <- x$t0
out <- density(c(obs, x$t), ...)
out$observed <- obs
out$call <- match.call()
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
#### plot method: the following copies stats::plot.density() code but
#### adds one new argument to draw abline(v=...) for the observed
#### statistic
`plot.vegandensity` <-
function (x, main = NULL, xlab = NULL, ylab = "Density", type = "l",
zero.line = TRUE, obs.line = TRUE, ...)
{
if (is.null(xlab))
xlab <- paste("N =", x$n, " Bandwidth =", formatC(x$bw))
if (is.null(main))
main <- deparse(x$call)
## change obs.line to col=2 (red) if it was logical TRUE
if (isTRUE(obs.line))
obs.line <- 2
plot.default(x, main = main, xlab = xlab, ylab = ylab, type = type,
...)
if (zero.line)
abline(h = 0, lwd = 0.1, col = "gray")
if (is.character(obs.line) || obs.line)
abline(v = x$observed, col = obs.line)
invisible(NULL)
}
`density.oecosimu` <-
function(x, ...)
{
.Deprecated("densityplot(permustats(<oecosimu.result>))",
package="vegan")
cols <- nrow(x$oecosimu$simulated)
if (cols > 1)
warning("'density' is meaningful only with one statistic, you have ", cols)
obs <- x$oecosimu$statistic
out <- density(rbind(obs, t(x$oecosimu$simulated)), ...)
out$observed <- obs
out$call <- match.call()
out$call[[1]] <- as.name("density")
class(out) <- c("vegandensity", class(out))
out
}
`densityplot.oecosimu` <-
function(x, data, xlab = "Simulated", ...)
{
.Deprecated("densityplot(permustats(<oecosimu.result>))",
package="vegan")
obs <- x$oecosimu$statistic
sim <- rbind(obs, t(x$oecosimu$simulated))
nm <- names(obs)[col(sim)]
densityplot( ~ as.vector(sim) | factor(nm, levels = unique(nm)),
xlab = xlab,
panel = function(x, ...) {
panel.densityplot(x, ...)
panel.abline(v = obs[panel.number()], ...)
},
...)
}
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