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Calculates the indicator value of species in a single cluster or environment type using the Murdoch Preference Function
murdoch(comm,type,minval=0,minplt=10)
# S3 method for murdoch
summary(object,pval=0.05,digits=3,…)
# S3 method for murdoch
plot(x,axtype=1,pval=0.05,…)
# S3 method for murdoch
print(x,digits = 5, ...)a matrix or data.frame of samples with species as columns and samples as rows
a logical vector with values of TRUE for samples in a specific cluster or type
a threshold minimum abundance value to count as a presence
the minimum number of presences to include a species in the calculation
and object of class ‘murdoch’
the maximum probability to include a species in the summary table
the number of digits to report
ancillary arguments to maintain compatibility with the generic summary function
an object of class ‘murdoch’
a switch to control scaling of the x axis in the plot. 1=number of plots in the data set, other = number of presences in the type
a list object of class ‘murdoch’ with components:
the minimum number of presences to be included
the number of plots a species occurs in
the plot membership vector for the type
the number of presences for species in the type
the number of absences of species in the type
the Murdoch value for species in the type
the probability of getting such a high murdoch value
Calculates the indicator value of species for a specific type using the modified Murdoch
statistic:
Probabilities are based on the hypergeometric distribution calculation of having as many or more presences in a type as observed.
# NOT RUN {
data(shoshveg) # returns a vegetation dataframe
dis.bc <- dsvdis(shoshveg,'bray/curtis') # returns a dissimilarity
# matrix
opt.5 <- optpart(5,dis.bc)
plot(murdoch(shoshveg,opt.5$clustering==1))
# }
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