Correlation and regression
- 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)
- 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
- 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")
- Programs for nonlinear parameter estimation by least squares,
maximum-likelihood and some robust methods.
- Multivariate Adaptive
- Fits multivariate datasets with splines surfaces. (P)
- 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).
- Package of smoothing spline subroutines with automatic knot selection.
- Nonlinear Statistical
- C++ implementation of least squares estimates for univariate and
multivariate nonlinear regression. (P)
- MATLAB routines
- Includes least squares, logistic and Poisson regression with related
- a Macintosh-based program for linear and non-linear regression,
with bootstrap estimation of errors of parameters and other options.
- 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
- 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
- Generates grid of variance ratios to plot confidence regions for two
parameters using Halperin's method.
- Fast implementations of nonparametric curve estimators including local
linear regression, the Nadaraya-Watson estimator and kernel density estimators.
- Computes ordinary and symmetrical least-squares regression lines for
bivariate data (orthogonal regression, reduced major axis, OLS bisector and
- 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+.
- Adaptive simulated annealing for global optimization of multivariate
nonlinear stochastic systems
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