Description Usage Arguments Value Author(s) Examples
View source: R/GenerateProbNumbers.R
this function randomly selects "times" positions in a vector according to a given distribution, either "power-law" or provided in the column "my.data$prob" It accepts a power-law distribution: y = c*x^k this parameterization is consistent with Hatton et al. 2015, who found a general scaling of k ~ 0.75 por prey and predator biomass across ecosystems globally hence the default k = 0.75. it also accepts a lognormal distribution with logmean and logsd and a gambin distribution with parameters gambin.alpha and gambin.maxoctave
1 2 3 | GenerateProbNumbers(times, choice.length = 100, dist = "power-law", c = 1,
k = 0.75, logmean = 0, logsd = 0.5, gambin.alpha = 2,
gambin.maxoctave = 8, cum.sum = 0, my.data = NULL)
|
times |
number of positions to be selected |
choice.length |
length of the vector to select positions from |
dist |
either "uniform", "power-law", "lognormal" or "gambin" |
c |
for the power law parametrization |
k |
exponent of the power law |
logmean |
mean of the lognormal distribution |
logsd |
standard deviation of the lognormal distribution |
gambin.alpha |
alpha value of the gambin distribution |
gambin.maxoctave |
value of the maximum octave of the gambin distribution -TODO- |
cum.sum |
cumulative sum of the returning values |
my.data |
dataframe specifying the distribution to sample from, instead of dist. Of the form my.data$prob |
numeric vector of length times
David Garc<c3><ad>a-Callejas, david.garcia.callejas@gmail.com
1 2 3 4 5 6 7 | t1 <- GenerateProbNumbers(100,c = 1, k = 0.75,cum.sum = 100)
hist(t1)
table(t1)
t2 <- GenerateProbNumbers(times = 2000, k = 0.25, cum.sum = 10000)
t3 <- GenerateProbNumbers(times = 80, choice.length = 100, dist = "gambin", gambin.alpha = 2, gambin.maxoctave = 8, cum.sum = 10000)
hist(t2)
hist(t3)
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