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1.1 root 1: basis functions, 214-216,218,224,227
2: bin smoother, 205,213
3: boundary knots, 215,227
4: brand, 202
5: building block, 200,208,225
6: categorical, 200
7: close, 206
8: computational aspects, 215,218
9: computational issues, 210
10: cubic smoothing spline, 217,219-220,227
11: cubic splines, 214
12: degrees of freedom, 211
13: derivation of smoothing splines, 227
14: effective dimension, 218
15: efficient kernel smoothing, 228
16: equivalent degrees of freedom, 213
17: equivalent kernel, 211,213,217,220,228
18: equivalent kernels, 211
19: estimating equations, 228
20: euclidean distance, 222
21: fine grid, 210,228
22: fitted smooth, 202,210
23: fundamental tradeoff between bias and variance, 202
24: hanning, 211
25: infinitely smooth, 204
26: interior knots, 213,215,217-218,227
27: kernel smooth, 210,228
28: kernel smoother, 208,210,222-223,225
29: kernel, 208,220
30: knots, 213
31: least-squares line, 206-207,218,227
32: linear, 211
33: local averaging, 202,220
34: locally weighted running-line smoothers, 220
35: locally-weighted running-lines, 208,225
36: loess smooth, 213
37: loess, 208,220-221
38: metric distance, 210
39: metric, 210
40: moving average, 200,206
41: multi-predictor smoothers, 224-225
42: multiple regression, 214,222
43: natural cubic spline, 218
44: natural splines, 214-215,218,227
45: natural-spline basis, 219
46: nearest neighbourhood, 206,221
47: nearest neighbours, 220,222
48: nearest, 222
49: neighbourhoods around, 202
50: nonparametric nature, 200
51: number, 215
52: parametric fitting, 205
53: parametric regression, 200,204,225
54: per\penalty \@M \ se, 225
55: piecewise cubic polynomials, 213-214
56: piecewise cubics, 216
57: piecewise polynomials, 213-214
58: piecewise, 213
59: predictor space, 223
60: rank distance, 210
61: regression smoothers, 211
62: regression splines, 205,213,215-217,224
63: rigid form, 200,204
64: robustified, 202
65: running mean, 200,206,210-211,213,222-223
66: running medians and enhancements, 210
67: running-lines smooth, 207-208,218
68: running-lines smoother, 207-208,221,225
69: running-mean and running-lines smoothers, 205
70: scatterplot smooth, 200,202,204
71: scatterplot smoother, 200,204,218,222,225
72: scatterplot smoothing, definition,200,202,204-205 204
73: semi-parametric regression, 228
74: single predictor, 200,222
75: smooth, 200
76: smoothers for multiple predictors, 222
77: smoothing parameter, 202,211,213,217,220-221,225
78: smoothing splines, 220,226,228
79: smoothing, 200,202,208,210-211,213,218,220-221,223-225,228
80: sorted values, 219
81: spaced data, 210-211
82: span, 221
83: standard gaussian density, 209
84: symmetric nearest neighbourhood, 206,221
85: symmetric nearest neighbours, 206,222
86: target point, 206,208,220-223
87: target value, 202,205,208
88: tensor product, 224
89: thin-plate spline, 223
90: time series, 211
91: tri-cube weight, 220
92: twicing, 211
93: unweighted running-lines smoother, 208
94: weight function, 210,220,223
95: weighted least-squares fit, 221
96: weighted least-squares, 208
97: when the knots are given, 216
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