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TITLE AND SUBTITLE T7 qnHl.p A Genetic Algorithm for Variable Knot Spline Fitting via Least Squares _____ 5. =UNDING NUMBERS
, 1998
"... fit * 3*v*33** "', suPPiEMENTAHYNOits,. thor(s) and should not be constroed as rinn rnnr "l2a. DISTRIBUTION / AVAILABILITY STATEM&N I Approved for public release: distribution unlimited. ..."
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fit * 3*v*33** "', suPPiEMENTAHYNOits,. thor(s) and should not be constroed as rinn rnnr "l2a. DISTRIBUTION / AVAILABILITY STATEM&N I Approved for public release: distribution unlimited.
Multivariate adaptive regression splines
 The Annals of Statistics
, 1991
"... A new method is presented for flexible regression modeling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number of basis functions as well as the parameters associated with each one (product degree and knot locations) are automaticall ..."
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Cited by 700 (2 self)
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A new method is presented for flexible regression modeling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number of basis functions as well as the parameters associated with each one (product degree and knot locations
Ideal spatial adaptation by wavelet shrinkage
 Biometrika
, 1994
"... With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or variable bandwidth kernel, to the unknown function. Estimation with the aid of an oracle o ers dramatic ad ..."
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Cited by 1269 (5 self)
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With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or variable bandwidth kernel, to the unknown function. Estimation with the aid of an oracle o ers dramatic
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
, 2001
"... Variable selection is fundamental to highdimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized ..."
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Cited by 948 (62 self)
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Variable selection is fundamental to highdimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized
Representing twentieth century spacetime climate variability, part 1: development of a 196190 mean monthly terrestrial climatology
 Journal of Climate
, 1999
"... The construction of a 0.58 lat 3 0.58 long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wetday frequency, mean temperature, diurnal temperature range, vapor pressur ..."
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Cited by 581 (13 self)
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The construction of a 0.58 lat 3 0.58 long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wetday frequency, mean temperature, diurnal temperature range, vapor
Flexible smoothing with Bsplines and penalties
 STATISTICAL SCIENCE
, 1996
"... Bsplines are attractive for nonparametric modelling, but choosing the optimal number and positions of knots is a complex task. Equidistant knots can be used, but their small and discrete number allows only limited control over smoothness and fit. We propose to use a relatively large number of knots ..."
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Cited by 405 (7 self)
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Bsplines are attractive for nonparametric modelling, but choosing the optimal number and positions of knots is a complex task. Equidistant knots can be used, but their small and discrete number allows only limited control over smoothness and fit. We propose to use a relatively large number
VERY HIGH RESOLUTION INTERPOLATED CLIMATE SURFACES FOR GLOBAL LAND AREAS
, 2005
"... We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered ..."
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Cited by 553 (8 self)
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from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thinplate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty
Selecting the Number of Knots For Penalized Splines
, 2000
"... Penalized splines, or Psplines, are regression splines fit by leastsquares with a roughness penaly. Psplines have much in common with smoothing splines, but the type of penalty used with a Pspline is somewhat more general than for a smoothing spline. Also, the number and location of the knots ..."
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Cited by 105 (10 self)
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of the knots of a Pspline is not fixed as with a smoothing spline. Generally, the knots of a Pspline are at fixed quantiles of the independent variable and the only tuning parameter to choose is the number of knots. In this article, the effects of the number of knots on the performance of Psplines
FREEKNOT SPLINES AND ADAPTIVE KNOT SELECTION
"... Conventional spline procedures have proven to be effective and useful for estimating smooth functions. However, these procedures find piecewise and inhomogeneous smooth functions difficult to handle. Conventional spline procedures often yield an overlysmooth curve in regions where the true functio ..."
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Cited by 1 (0 self)
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function or its derivative are discontinuous. To fully realize the potential of the spline methodology, this article proposes a function estimation procedure that uses adaptive freeknot splines and allows for multiple knots to be replaced at the same location and between design points. The article also
Constrained Approximation By Splines With Free Knots
"... In this paper, a method that combines shape preservation and least squares approximation by splines with free knots is developed. Besides the coefficients of the spline a subset of the knot sequence, the socalled free knots, is included in the optimization process resulting in a nonlinear least squ ..."
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Cited by 4 (0 self)
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squares problem in both the coefficients and the knots. The original problem, a special case of a constrained semilinear least squares problem, is reduced to a problem that has only the knots of the spline as variables. The reduced problem is solved by a generalized GaussNewton method. Special emphasize
Results 1  10
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1,513