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"Logical" -> "Scalar logical" as appropriate to match rest of docs
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R/layer_cdc_flatline_quantiles.R

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#' These samples are spaced evenly on the (0, 1) scale, F_X(x) resulting in
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#' linear interpolation on the X scale. This is achieved with
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#' [stats::quantile()] Type 7 (the default for that function).
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#' @param symmetrize Logical. If `TRUE`, does two things: (i) forces the
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#' @param symmetrize Scalar logical. If `TRUE`, does two things: (i) forces the
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#' "empirical" CDF of residuals to be symmetric by pretending that for every
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#' actually-observed residual X we also observed another residual -X, and (ii)
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#' at each ahead, forces the median simulated value to be equal to the point
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#' simulating the next ahead. This forces any 1-ahead predictive intervals to
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#' be symmetric about the point prediction, and encourages larger aheads to be
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#' more symmetric.
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#' @param nonneg Logical. Force all predictive intervals be non-negative.
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#' @param nonneg Scalar logical. Force all predictive intervals be non-negative.
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#' Because non-negativity is forced _before_ propagating forward, this has
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#' slightly different behaviour than would occur if using [layer_threshold()].
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#' Thresholding at each ahead takes place after any shifting from

man/layer_cdc_flatline_quantiles.Rd

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