dgambin | R Documentation |
Density, distribution function, quantile function and random generation for the mixture gambin distribution.
dgambin(x, alpha, maxoctave, w = 1, log = FALSE) pgambin(q, alpha, maxoctave, w = 1, lower.tail = TRUE, log.p = FALSE) rgambin(n, alpha, maxoctave, w = 1) qgambin(p, alpha, maxoctave, w = 1, lower.tail = TRUE, log.p = FALSE) gambin_exp(alpha, maxoctave, w = 1, total_species)
x |
vector of (non-negative integer) quantiles. |
alpha |
The shape parameter of the GamBin distribution. |
maxoctave |
The scale parameter of the GamBin distribution - which octave is the highest in the empirical dataset? |
w |
A vector of weights. Default, a single weight. This vector must of the same length as alpha. |
log |
logical; If |
q |
vector of quantiles. |
lower.tail |
logical; if |
log.p |
logical; if |
n |
number of random values to return. |
p |
vector of probabilities. |
total_species |
The total number of species in the empirical dataset |
dgambin
gives the distribution function of a mixture gambin, so all octaves sum to 1.
gambin_exp
multiplies this by the total number of species to give the expected GamBin distribution in units of species,
for comparison with empirical data.
A vector with length MaxOctave + 1 of the expected number of species in each octave
Matthews, T. J., Borregaard, M. K., Gillespie, C. S., Rigal, F., Ugland, K. I., Krüger, R. F., . . . Whittaker, R. J. (2019) Extension of the gambin model to multimodal species abundance distributions. Methods in Ecology and Evolution, doi:10.1111/2041-210X.13122
Matthews, T.J., Borregaard, M.K., Ugland, K.I., Borges, P.A.V, Rigal, F., Cardoso, P. and Whittaker, R.J. (2014) The gambin model provides a superior fit to species abundance distributions with a single free parameter: evidence, implementation and interpretation. Ecography 37: 1002-1011.
## maxoctave is 4. So zero for x = 5 dgambin(0:5, 1, 4) ## Equal weightings between components dgambin(0:5, alpha = c(1,2), maxoctave = c(4, 4)) ## Zero weight on the second component, i.e. a 1 component model dgambin(0:5, alpha = c(1,2), maxoctave = c(4, 4), w = c(1, 0)) expected = gambin_exp(4, 13, total_species = 200) plot(expected, type = "l") ##draw random values from a gambin distribution x = rgambin(1e6, alpha = 2, maxoctave = 7) x = table(x) freq = as.vector(x) values = as.numeric(as.character(names(x))) abundances = data.frame(octave=values, species = freq) fit_abundances(abundances, no_of_components = 1)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.