- 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.
**(P)** - 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.
**(P)** - ODRPACK
- Orthogonal distance nonlinear regression for data weighted by known
measurement errors
**(P)** - Bivariate linear regression with errors in both variables
- Three short Fortran programs giving similar results, by Fionn Murtagh of Queens University. (Look under "Various other programs")
- NLR
- Programs for nonlinear parameter estimation by least squares,
maximum-likelihood and some robust methods.
**(P)** - Multivariate Adaptive Regression Splines
- Fits multivariate datasets with splines surfaces.
**(P)** - FITPACK
- Fits curves and surfaces using splines under tension
**(P)** - Least squares codes
- A extensive collection of Fortran 90 codes for unconstrained linear and nonlinear least-squares, ridge regression, fitting ellipses to (x,y) data, logistic regression, and more. From Alan J. Miller (CSIRO).
- DIERCKX
- Package of smoothing spline subroutines with automatic knot selection.
**(P)** - Nonlinear Statistical Models
- C++ implementation of least squares estimates for univariate and
multivariate nonlinear regression.
**(P)** - MATLAB routines
- Includes least squares, logistic and Poisson regression with related
functions.
**(P)** - Regress+
- a Macintosh-based program for linear and non-linear regression,
with bootstrap estimation of errors of parameters and other options.
**P** - Measurement error regression
- Three versions of errors-in-variables bivariate linear regression: York, Fasano & Vio, Ripley.
- Errors-in-Variables Model
- Least squares linear and nonlinear parameter estimation with errors in the predictor variables and the dependent variable.
- Partial correlation for censored data
- A test for partial correlation between three variables, any or all of which are subject to censoring, based on a generalized Kendall's tau.
- Generalized additive models
- Generalized additive models fitting a variety of models (Gaussian, Binomial, Poisson, Gamma, Cox) using cubic smoothing splines.
- Smoothing spline analysis of variance (GRKPACK)
- Nonparametric estimation of generalized linear model regression surfaces by fitting smoothing spline ANOVA models for Poisson and other data, with Bayesian confidence intervals.
- Bivariate linear regression
- Robust regression by least absolute deviations.
- Confidence intervals for nonlinear regression
- Generates grid of variance ratios to plot confidence regions for two parameters using Halperin's method.
- Nonparametric regression
- Fast implementations of nonparametric curve estimators including local linear regression, the Nadaraya-Watson estimator and kernel density estimators.
- SLOPES
- Computes ordinary and symmetrical least-squares regression lines for bivariate data (orthogonal regression, reduced major axis, OLS bisector and mean OLS).
- Linear regression with measurement errors and scatter
- Weighted ordinary least squares line with heteroscedastic measurement errors and homoscedastic intrinsic scatter in the dependent variable. Also includes code in SLOPES.
- Linear regression with measurement errors
- Code calculationg simultaneous confidence bands for linear regression with heteroscedastic errors using bootstrap resampling, based on Faraway & Sun (JASA 1995). Code in LISP-STAT and S+.
- ASA
- Adaptive simulated annealing for global optimization of multivariate nonlinear stochastic systems

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