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# calculate shannon-entropy -sum(freqs * log2(freqs)) [1] 0.940286 As a side note, the function entropy.empirical is in the entropy package where you set the units to log2 allowing some more flexibility. Example: entropy.empirical(freqs, unit="log2") [1] 0.940286
The entropy function allows to estimate entropy from observed counts by a variety of methods: method="ML":maximum likelihood, see entropy.empirical. method="MM":bias-corrected maximum likelihood, see entropy.MillerMadow. method="Jeffreys": entropy.Dirichlet with a=1/2. method="Laplace": entropy.Dirichlet with a=1.
Now, the question is: assuming that the following is the algorithm used to calculate the entropy – taken from Wikipedia $$ \mathrm{H}(X) = -\sum_{i} {\mathrm{P}(x_i) \log_b \mathrm{P}(x_i)} $$ my questions are the following.
7 Φεβ 2016 · when I calculate entropy for attribute B the result give me NaN that is due to zero (0) (log2 (0) is error ) . in such situation how can I fix this error or how can make H1 give me zero instead of NaN. ifelse(is.na(entropy), 0, entropy) should work. There is a package called 'entropy' in r if it works for you.
16 Ιαν 2023 · Entropy changes are fairly easy to calculate so long as one knows initial and final state. For example, if the initial and final volume are the same, the entropy can be calculated by assuming a reversible, isochoric pathway and determining an expression for \(\frac{dq}{T}\).
1 Απρ 2011 · I tried to apply an entropy to time series of daily P/L on equity portfolios (developed markets). I found out that there is a strong correlation among entropy and other risk measures such as standard deviation, VaR and CVaR.
7 Σεπ 2023 · I'm using R poLCA to run a latent class model with 4 categorical indicators (3 levels, 3 levels, 9 levels and 5 levels). As poLCA doesn't compute relative entropy, I have found two formulas for calculating it manually from the results, both presented in this answer here.
