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- W1978277789 abstract "We suggest a one-dimensional jump-detection algorithm based on local polynomial fitting for jumps in regression functions (zero-order jumps) or jumps in derivatives (first-order or higherorder jumps). If jumps exist in the mth-order derivative of the underlying regression function, then an (m + 1). Order polynomial is fitted in a neighborhood of each design point. We then characterize the jump information in the coefficients of the highest-order terms of the fitted polynomials and suggest an algorithm for jump detection. This method is introduced briefly for the general setup and then presented in detail for zero-order and first-order jumps. Several simulation examples are discussed. We apply this method to the Bombay (India) sea-level pressure data." @default.
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- W1978277789 date "1998-05-01" @default.
- W1978277789 modified "2023-10-13" @default.
- W1978277789 title "A Local Polynomial Jump-Detection Algorithm in Nonparametric Regression" @default.
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- W1978277789 doi "https://doi.org/10.2307/1270648" @default.
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