Correlation and regression

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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