renyi  find renyiaccum finds these statistics with accumulating sites.renyi(x, scales = c(0, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64, Inf),
   hill = FALSE)
## S3 method for class 'renyi':
plot(x, ...)
renyiaccum(x, scales = c(0, 0.5, 1, 2, 4, Inf), permutations = 100, 
    raw = FALSE, collector = FALSE, subset, ...)
## S3 method for class 'renyiaccum':
plot(x, what = c("Collector", "mean", "Qnt 0.025", "Qnt 0.975"),
    type = "l", 
    ...)
## S3 method for class 'renyiaccum':
persp(x, theta = 220, col = heat.colors(100), zlim, ...)
rgl.renyiaccum(x, rgl.height = 0.2, ...)FALSE then return summary statistics of
    permutations, and if TRUE then returns the individual
    permutations.raw = TRUE.FALSE.type = "l" means lines.persp.persp.renyi and
    to graphical functions.renyi returns a data frame of selected
  indices.  Function renyiaccum with argument raw = FALSE
  returns a three-dimensional array, where the first dimension are the
  accumulated sites, second dimension are the diversity scales, and
  third dimension are the summary statistics mean, stdev,
  min, max, Qnt 0.025 and Qnt 0.975.  With
  argument raw = TRUE the statistics on the third dimension are
  replaced with individual permutation results.diversity indices are special cases of
    The plot method for renyi uses 
  Function renyiaccum is similar to specaccum but
  finds scales
  for random permutations of accumulated sites.  Its plot
  function uses xyplot to
  display the accumulation curves for each value of scales in a
  separate panel.  In addition, it has a persp method to plot the
  diversity surface against scale and number and sites. Dynamic graphics
  with rgl.renyiaccum use persp with a mesh showing the empirical confidence levels.
Hill, M.O. (1973). Diversity and evenness: a unifying notation and its consequences. Ecology 54, 427--473.
   Kindt R, Van Damme P, Simons AJ. 2006. Tree diversity in western
   Kenya: using profiles to characterise richness and 
   evenness. Biodiversity and Conservation 15: 1253-1270.
   
   
diversity for diversity indices, and
  specaccum for ordinary species accumulation curves, and
  xyplot, persp and
  rgl for controlling graphics.data(BCI)
i <- sample(nrow(BCI), 12)
mod <- renyi(BCI[i,])
plot(mod)
mod <- renyiaccum(BCI[i,])
plot(mod, as.table=TRUE, col = c(1, 2, 2))
persp(mod)Run the code above in your browser using DataLab