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Density estimation, smoothing & splines

LOESS
    Locally-weighted regression for irregularly spaced multivariate data estimating regression curves and surfaces by a local smoothing procedure. Manual includes application to velocity structure of spiral galaxy.  By W. Cleveland and colleagues, distributed by Statlib and Netlib.

LOCFIT
    Package for multivariate nonlinear regression and adaptive smoothing developed at Bell Labs and based on the book `Local Regression and Likelihood' (Springer, 1999). Similar to LOESS but with more flexible bandwidth options; includes cross-validation and other model assessment tools. Code available in C and within the S-plus, S and R software environments. By J. Sun of Case Western Reserve University.

FITPACK
    Fits curves and surfaces using splines under tension. Distributed by GAMS and Netlib.

DIERCKX
    Package of smoothing spline subroutines with automatic knot selection.  Distributed by GAMS and Netlib.

GRKPACK
    Nonparametric estimation of generalized linear model regression surfaces by fitting smoothing spline ANOVA models for Poisson and other data, with Bayesian confidence intervals.  By Y. Wang of University of Wisconsin, distributed by Statlib.

Nonparametric regression
    Fast implementations of nonparametric curve estimators including local linear regression, the Nadaraya-Watson estimator and kernel density estimators.  By J. Fan of University of North Caroline, distributed by Statlib.

Kernel density estimation
    Gaussian smoothing using fast Fourier transform.  Applied Statistics algorithm #176.

Mixture models
    Maximum likelihood estimates of mixture of normal, Poisson or other distributions. Applied Statistics algorithm #203.

Mixture models
    Maximum likelihood estimates of mixture of normal, Poisson or other distributions.  Applied Statistics algorithm #221.

Dip statistic
    Computes Hartigan's statistic to test for unimodality. Applied Statistics algorithm #217.

Univariate kernel smoother
    Calculates probabilities of bins for a multinomial vector using a quadratic kernel with smoothing determined from cross-validation.  By J. Dong & J. Simonoff of New York University, distributed by Statlib.