Methods in Ecology and Evolution 4(11):1091-1100.Ĭhao, A., Gotelli, N. Entropy and the species accumulation curve: a novel entropy estimator via discovery rates of new species. Environmental and Ecological Statistics 10(4): 429-443.Ĭhao, A., Wang, Y. Nonparametric estimation of Shannon's index of diversity when there are unseen species in sample. Journal of Physics A: Mathematical and Theoretical 41(202001): 1-9.Ĭhao, A. If Unveiling is "None", then the asymptotic estimation of entropy is made using the chosen Correction, else the asymtpotic distribution of the community is derived and its estimated richness adjusted so that the entropy of a sample of this distribution of the size of the actual sample has the entropy of the actual sample.īonachela, J. If its first argument is an abundance vector, an integer vector or a numeric vector which does not sum to 1, the bias corrected function bcShannon is called.Įntropy can be estimated at a specified level of interpolation or extrapolation, either a chosen sample size or sample coverage (Chao et al., 2014), rather than its asymptotic value.Įxtrapolation relies on the estimation of the asymptotic entropy. The functions are designed to be used as simply as possible. Using MetaCommunity mutual information, Chao, Wang and Jost (2013) calculate reduced-bias Shannon beta entropy (see the last example below) with better results than the Chao and Shen estimator, but community weights cannot be arbitrary: they must be proportional to the number of individuals. More estimators can be found in the entropy package. Should be set to FALSE to save time when the arguments have been checked elsewhere.īias correction requires the number of individuals to estimate sample Coverage.Ĭorrection techniques are from Miller (1955), Chao and Shen (2003), Grassberger (1988), Grassberger (2003), Schurmann (2003), Holste et al. Logical if TRUE, the function arguments are verified.
Used only for extrapolation.Īdditional arguments. "Rarefy" is the default value to estimate the number of species such that the entropy of the asymptotic distribution rarefied to the observed sample size equals the observed entropy of the data. RCorrectionĪ string containing a correction recognized by Richness to evaluate the total number of species in as.ProbaVector. If "None", the asymptotic distribution is not unveiled and only the asymptotic estimator is used. UnveilingĪ string containing one of the possible unveiling methods to estimate the probabilities of the unobserved species in as.ProbaVector: "geom" (the unobserved species distribution is geometric) is the default value. PCorrectionĪ string containing one of the possible corrections to estimate a probability distribution in as.ProbaVector: "Chao2015" is the default value. Entropy interpolation relies on the estimation of Abundance Frequence Counts: then, Correction is passed to AbdFreqCount as its Estimator argument. Entropy extrapolation require its asymptotic estimation depending on the choice of Correction. It may be an a chosen sample size (an integer) or a sample coverage (a number between 0 and 1).
The level of interpolation or extrapolation. CorrectionĪ string containing one of the possible asymptotic estimators: "None" (no correction), "ChaoShen", "GenCov", "Grassberger", "Grassberger2003", "Schurmann", "Holste", "Bonachela", "Miller", "ZhangHz", "ChaoJost", "Marcon", "UnveilC", "UnveiliC", "UnveilJ" or "Best", the default value. Contains either abundances or probabilities. NorPĪ numeric vector, an integer vector, an abundance vector ( AbdVector) or a probability vector ( ProbaVector). A numeric vector containing species abundances.
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