Statistics and Econometrics |
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Code for "Invariant Small Sample Confidence Intervals For The Difference Of Two Success Probabilities" and "Bootstrap Prediction and Confidence Bands: a Superior Statistical Method for Analysis of Gait Data", by Thomas Santner.
Code by Laurie Davies for modality of spectral densities, ANOVA, and nonparametric regression: runs, taut strings, and local extremes.
See Applied Statistics (algorithms of the Royal Statistical Society) and General Archives for a considerable amount of Fortran code.
By Gabriele Fiorentini, Giorgio Calzolari, and Lorenzo Panattoni, for a 1996 paper in the Journal of Applied Econometrics.
Model-based clustering, discriminant analysis, and density estimation including hierarchical clustering and EM for parameterized Gaussian mixtures + Poisson noise. Written in Fortran and interfaced to the S-PLUS commercial software package and the R language. By Chris Fraley and Adrian Raftery.
Fits a mixture model of multivariate normal or t-distributions to a user supplied data set via the EM algorithm. By Geoff McLachlan.
NOCOM estimates the parameters (means, variance, proportions of components) of a mixture of normal distributions for independent observations (quantitative data). COMPMIX assumes a mixture of normal distributions, with parameters for each component in that mixture. The COMPMIX program then calculates the conditional probability, given an observed value, that it belongs to the i-th component.
Mixture modelling by Minimum Message Length (MML).
Code in C and Fortran for the analysis of time series with methods based on the theory of nonlinear deterministic dynamical systems (chaos).
Univariate and multivariate spline regression, by Dolph Schluter.
Computers /
Algorithms /
Pseudorandom_Numbers
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