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Correct the documentation to reflect more general input type
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src/signalcorr.jl

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@@ -233,7 +233,7 @@ end
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"""
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crosscov!(r, x, y, lags; demean=true)
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Compute the cross covariance function (CCF) between real-valued vectors or matrices
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Compute the cross covariance function (CCF) between vectors or matrices
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`x` and `y` at `lags` and store the result in `r`. `demean` specifies whether the
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respective means of `x` and `y` should be subtracted from them before computing their
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CCF.
@@ -343,7 +343,7 @@ end
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"""
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crosscov(x, y, [lags]; demean=true)
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Compute the cross covariance function (CCF) between real-valued vectors or
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Compute the cross covariance function (CCF) between vectors or
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matrices `x` and `y`, optionally specifying the `lags`. `demean` specifies
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whether the respective means of `x` and `y` should be subtracted from them
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before computing their CCF.
@@ -384,7 +384,7 @@ crosscov(x::AbstractVecOrMat, y::AbstractVecOrMat; demean::Bool=true) =
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"""
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crosscor!(r, x, y, lags; demean=true)
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Compute the cross correlation between real-valued vectors or matrices `x` and `y` at
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Compute the cross correlation between vectors or matrices `x` and `y` at
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`lags` and store the result in `r`. `demean` specifies whether the respective means of
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`x` and `y` should be subtracted from them before computing their cross correlation.
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@@ -504,7 +504,7 @@ end
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"""
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crosscor(x, y, [lags]; demean=true)
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507-
Compute the cross correlation between real-valued vectors or matrices `x` and `y`,
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Compute the cross correlation between vectors or matrices `x` and `y`,
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optionally specifying the `lags`. `demean` specifies whether the respective means of
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`x` and `y` should be subtracted from them before computing their cross correlation.
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@@ -613,7 +613,7 @@ end
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"""
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pacf(X, lags; method=:regression)
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Compute the partial autocorrelation function (PACF) of a real-valued vector
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Compute the partial autocorrelation function (PACF) of a vector
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or matrix `X` at `lags`. `method` designates the estimation method. Recognized
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values are `:regression`, which computes the partial autocorrelations via successive
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regression models, and `:yulewalker`, which computes the partial autocorrelations

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