All functions |
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Perform 2D linear approximation |
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Convert |
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Check the input data and return a list in the right format. |
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Perform an estimation of the covariance with local linear smoothers. |
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Perform an estimation of the covariance with local linear smoothers. |
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Perform an estimation of the covariance with smoothing splines. |
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Perform an estimation of the bandwidth for the estimation of the covariance. |
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Perform an estimation of the bandwidth for the estimation of the mean. |
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Perform an estimation of the bandwidth for the estimation of the covariance |
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Perform an estimation of the bandwidth for the estimation of the mean. |
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Perform the estimation of the constant \(L_0\). |
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Perform the estimation of the variance \(Var(X_{s}X_{t)}\). |
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Perform the smoothing of an individual curve. |
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Perform the estimation of the moments. |
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Perform a recursive estimation of the parameters over a grid of points for the estimation of the covariance. |
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Perform a recursive estimation of the parameters over a grid of points for the estimation of the mean. |
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Perform a recursive estimation of the parameters. |
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Perform an estimation of the regularity \(H_0\). |
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Perform an estimation of the standard deviation of the noise. |
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Perform an estimation of \(Var(X_{t_0)}\). |
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Convert |
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funestim: A package for the mean estimation of a set of curves. |
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Convert |
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Compute the values for some kernels. |
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Convert comprehensive lists into |
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Convert comprehensive lists into |
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Convert comprehensive lists into |
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Logarithmic sequence generation. |
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Perform an estimation of the mean with local linear smoothers. |
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Perform an estimation of the mean with local linear smoothers. |
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Perform an estimation of the mean with smoothing splines. |
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Convert |
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Test whether the observation points are in the neighborhood. |
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Perform a pre-smoothing of the data. |
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Perform a non-parametric smoothing of a set of curves for covariance estimation. |
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Perform a non-parametric smoothing of a set of curves for mean estimation. |