| fCressieRead | R Documentation | 
This function obtains the Cressie and Read statistics introduced by Noel Cressie and Timothy Read. It is a method for quantifying species biodiversity that can be adapted to the context of onomastics.
fCressieRead(x, number, population, ni, location, lambda)
x | 
 dataframe of the data values.  | 
number | 
 name of a variable which represents number of individuals of each species.  | 
population | 
 name of variable which represents total number of individuals.  | 
ni | 
 name of variable which represent number of species.  | 
location | 
 name of variable which represent represents the grouping element.  | 
lambda | 
 free parameter.  | 
For a community i, Cressie and Read (1984) introduced the following parametric form for a generalised statistic
I_n (\lambda) = \frac{2}{\lambda(\lambda+1)}  \sum_{k\in S_i} { n_{ki} \left[ \left(\frac{n_{ki}}{n/S_i}\right)^\lambda-1\right]}, where n_{ki} represents the number of individuals of species k in a sample (in the population is N_{ki}), S_i represents all species at the community, species richness, and \lambda is a free parameter.
Varying the value of \lambda gets different statistics. 
If \lambda= -1 and \lambda= 0, I_n(\lambda) is not defined, but in any case, limits \lambda = -1 and \lambda = 0 can be taken.
In onomastic context, n_{ki} (\approx N_{ki}) denotes the absolute frequency of surname k in region i (\approx community diversity context i).
A dataframe containing the following components:
location | 
 represents the grouping element, for example the communities / regions.  | 
cressieRead | 
 the value of Cressie and Read statistics.  | 
Maria Jose Ginzo Villamayor
Cressie, Noel and Read, Timothy RC (1984) Multinomial goodness-of-fit tests. Computational Statistics and Data Analysis, 46(3), 440–464.
fHill
data(surnamesgal14)
result = fCressieRead(x= surnamesgal14 , number="number",
population="population", location = "muni", ni="ni",
lambda = 2)
result
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