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Annotation of researchv10dc/vol2/index/chap2.terms, revision 1.1.1.1

1.1       root        1: smoothing splines
                      2: running mean
                      3: target point
                      4: interior knots
                      5: smoothing parameter
                      6: running-lines smooth
                      7: equivalent kernels
                      8: equivalent kernel
                      9: basis functions
                     10: running-lines smoother
                     11: least-squares line
                     12: kernel smoothers
                     13: kernel smoother
                     14: cubic smoothing spline
                     15: target value
                     16: symmetric nearest neighbourhood
                     17: spaced data
                     18: scatterplot smoother
                     19: rigid form
                     20: nearest neighbours
                     21: nearest neighbourhood
                     22: natural splines
                     23: matrix
                     24: locally-weighted running-lines
                     25: kernel smooth
                     26: data points
                     27: weighted least-squares fit
                     28: weight function
                     29: unweighted running-lines smoother
                     30: time series
                     31: three interior knots
                     32: third derivative
                     33: symmetric nearest neighbours
                     34: symmetric nearest neighbourhoods
                     35: standard Gaussian density
                     36: single predictor
                     37: scatterplot smoothing
                     38: scatterplot smoothers
                     39: scatterplot smooth
                     40: predictor space
                     41: piecewise polynomials
                     42: piecewise cubics
                     43: piecewise cubic polynomials
                     44: parametric fitting
                     45: nearest neighbourhoods
                     46: natural cubic splines
                     47: natural cubic spline
                     48: multiple regression
                     49: multi-predictor smoothers
                     50: moving average
                     51: matrix containing
                     52: interested reader
                     53: fitted smooth
                     54: fine grid
                     55: evaluated-splines
                     56: cubic-spline basis functions
                     57: building block
                     58: boundary knots
                     59: bin smoother
                     60: bibliographic notes
                     61: Fig. shows
                     62: Euclidean distance
                     63: Smoothing
                     64: What is a smoother?
                     65: Scatterplot smoothing: definition
                     66: Parametric Regression
                     67: Bin smoothers
                     68: Running-mean  and running-lines smoothers
                     69: Kernel smoothers
                     70: Computational issues
                     71: Running medians and enhancements
                     72: Equivalent kernels
                     73: Regression splines
                     74: Computational aspects
                     75: Cubic smoothing splines
                     76: Computational aspects
                     77: Locally weighted running-line smoothers
                     78: Smoothers for multiple predictors
                     79: {\sl smoother}
                     80: {\sl nonparametric} nature
                     81: {\sl smooth}
                     82: {\sl scatterplot smoothing}
                     83: {\sl categorical}
                     84: {\sl smoothing}
                     85: {\sl local averaging}
                     86: {\sl neighbourhoods} around
                     87: {\sl brand}
                     88: {\sl smoothing parameter}
                     89: {\sl fundamental tradeoff between bias and variance}
                     90: {\em robustified}
                     91: {\sl infinitely smooth}
                     92: {\sl close}
                     93: {\sl symmetric nearest neighbourhood}
                     94: {\sl running mean}
                     95: {\sl nearest neighbourhood}
                     96: {\sl moving average}
                     97: {\sl smoother}
                     98: {\sl running lines smoother}
                     99: {\sl weighted} least-squares
                    100: {\sl loess}
                    101: {\sl kernel}
                    102: {\sl metric} distance
                    103: {\sl metric}
                    104: {\sl rank} distance
                    105: {\em Hanning}
                    106: {\em twicing}
                    107: {\em regression smoothers}
                    108: {\em linear}
                    109: {\em degrees of freedom}
                    110: {\sl equivalent kernels}
                    111: {\sl linear}
                    112: {\em equivalent kernel}
                    113: {\em loess} smooth
                    114: {\sl equivalent degrees of freedom}
                    115: {\sl piecewise}
                    116: {\sl knots}
                    117: {\sl cubic} splines
                    118: {\sl number}
                    119: {\sl when the knots are given}
                    120: {\sl natural cubic spline}
                    121: {\sl effective} dimension
                    122: {\sl sorted} values
                    123: {\sl natural-spline} basis
                    124: {\sl local averaging}
                    125: {\sl kernel}
                    126: {\sl loess}
                    127: {\sl tri-cube} weight
                    128: {\sl span}
                    129: {\sl loess}
                    130: {\sl nearest neighbours}
                    131: {\sl Nearest}
                    132: {\sl thin-plate spline}
                    133: {\sl tensor product}
                    134: {\sl per~se}
                    135: {\sl Updating formula for running-line smooth}
                    136: {\sl Basis for natural splines}
                    137: {\sl Derivation of smoothing splines
                    138: {\sl Semi-parametric regression
                    139: {\sl estimating} equations
                    140: {\sl Efficient kernel smoothing

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