diff --git a/docs/src/Guide/Multiscale_Cross_Entropies.md b/docs/src/Guide/Multiscale_Cross_Entropies.md index a83c04e..f4faf08 100644 --- a/docs/src/Guide/Multiscale_Cross_Entropies.md +++ b/docs/src/Guide/Multiscale_Cross_Entropies.md @@ -11,8 +11,8 @@ To do so, we again use the `MSobject` function to pass a multiscale object (`Mob Multiscale cross-entropy functions have three positional arguments: - 1. the first data seuqence, `Sig1` (an Nx1 matrix), - 2. the second data seuqence, `Sig2` (an Nx1 matrix), + 1. the first data seuqence, `Sig1` (a vector of >10 elements), + 2. the second data seuqence, `Sig2` (a vector of > 10 elements), 2. the multiscale entropy object, `Mobj`. diff --git a/src/_RangEn.jl b/src/_RangEn.jl index 49a4ec6..9b4caff 100644 --- a/src/_RangEn.jl +++ b/src/_RangEn.jl @@ -9,17 +9,17 @@ using Statistics: mean using the sample entropy algorithm and the following default parameters: embedding dimension = 2, time delay = 1, radius threshold = 0.2, logarithm = natural. - Rangx, A, B = RangEn(Sig, keyword = value, ...) + Rangx, A, B = RangEn(Sig::AbstractArray{T,1} where T<:Real; m::Int=2, tau::Int=1, r::Real=0.2, Methodx::String="SampEn", Logx::Real=exp(1)) Returns the range entropy estimates (`Rangx`) for dimensions = `m` estimated for the data sequence (`Sig`) using the specified keyword arguments: # Arguments: - `m` - Embedding Dimension, a positive integer - `tau` - Time Delay, a positive integer - `r` - Radius Distance Threshold, a positive value between 0 and 1 - `Methodx` - Base entropy method, either 'SampEn' [default] or 'ApEn' - `Logx` - Logarithm base, a positive scalar + `m` - Embedding Dimension, a positive integer\n + `tau` - Time Delay, a positive integer\n + `r` - Radius Distance Threshold, a positive value between 0 and 1\n + `Methodx` - Base entropy method, either 'SampEn' [default] or 'ApEn'\n + `Logx` - Logarithm base, a positive scalar \n # See also `ApEn`, `SampEn`, `FuzzEn`, `MSEn`