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1.1 root 1: {\sl smoother}
2: {\sl nonparametric} nature
3: {\sl smooth}
4: RIGHT
5: {\sl scatterplot smoothing}
6: {\sl categorical}
7: {\sl smoothing}
8: {\sl local averaging}
9: {\sl neighbourhoods} around
10: {\sl brand}
11: {\sl smoothing parameter}
12: {\sl fundamental tradeoff between bias and variance}
13: {\em robustified}
14: {\sl infinitely smooth}
15: {\sl close}
16: {\sl symmetric nearest neighbourhood}
17: {\sl running mean}
18: {\sl nearest neighbourhood}
19: {\sl moving average}
20: {\sl smoother}
21: RIGHT
22: {\sl running lines smoother}
23: {\sl weighted} least-squares
24: {\sl loess}
25: {\sl kernel}
26: {\sl metric} distance
27: {\sl metric}
28: {\sl rank} distance
29: {\em Hanning}
30: {\em twicing}
31: {\em regression smoothers}
32: {\em linear}
33: {\em degrees of freedom}
34: {\sl equivalent kernels}
35: {\sl linear}
36: {\em equivalent kernel}
37: {\em loess} smooth
38: {\sl equivalent degrees of freedom}
39: {\sl piecewise}
40: {\sl knots}
41: {\sl cubic} splines
42: {\sl number}
43: {\sl when the knots are given}
44: {\sl natural cubic spline}
45: {\sl effective} dimension
46: {\sl sorted} values
47: {\sl natural-spline} basis
48: {\sl local averaging}
49: {\sl kernel}
50: {\sl loess}
51: {\sl tri-cube} weight
52: {\sl span}
53: {\sl loess}
54: {\sl nearest neighbours}
55: {\sl Nearest}
56: {\sl thin-plate spline}
57: {\sl tensor product}
58: {\sl per~se}
59: {\sl Updating formula for running-line smooth}
60: {\sl Basis for natural splines}
61: {\sl Derivation of smoothing splines ^{Reinsch (1967)}.}
62: {\sl Semi-parametric regression ^^{Green, P.J.}^^{Jennison,
63: {\sl estimating} equations
64: {\sl Efficient kernel smoothing ^{Silverman (1982)},
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