GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language for settings where long running programs are required. It is useful to think of Octave as a free alternative to Matlab. The community of users is large and productive, resulting in many freely available programs based on Octave. Visit the homepage at:
Complex Surveys often require analysis techniques based on what is known as “Design Based” methods. This is a special branch of Statistics concerned with finite populations and complex survey designs with supporting estimation methods. Options to address this area of survey tools can be found in commerical packages such as SUDAAN, SAS, SPSS, STATA and others to varying degree. WesVar overlaps these options and offers jackknife and balanced repeated replication(BRR)methods to estimate variances of survey estimates. These methods correctly account for the effects of multistage complex survey designs with stratifed and unequal selection probabilities. For more information see:
SuperLU contains a set of subroutines to solve a sparse linear system
A*X=B. This is often at the heart of many research computing tasks in science, engineering, statistical software. It uses Gaussian elimination with partial pivoting (GEPP). The columns of A may be preordered before factorization; the preordering for sparsity is completely separate from the factorization. SuperLU is implemented in ANSI C, and must be compiled with standard
ANSI C compilers. It provides functionality for both real and complex matrices, in both single and double precision. In addition, a Matlab MEX interface option is available for access from within Matlab. Additional info may be found at: http://crd.lbl.gov/~xiaoye/SuperLU/
CAGED is a unique Bayesian statistical tool for gene expression profiles that uses a time series approach to clustering. Markov models are used for within sequence representation and similiarity measures, such as entropy-based distances, are available for between gene sequence clustering purposes. Gene clusters are chosen on the basis of highest marginal likelihoods. CAGED is freely available after registration. For more info: http://genomethods.org/caged/
MCMCGLMM is a C based program for the fitting of Generalized Linear Models via Monte Carlo Markov Chain sampling. Powered-Exponential and Matern spatial covariance functions are available to capture spatial effects, and right and left censoring is available for Guassian and Binomial-logit models.
Active developement of this software has stopped, and further developement has shifted to R as geoRglm. There is still some functionality in the C code not yet transfered to geoRglm.
All things being equal, and for large datasets, the compiled version will execute much faster than geoRglm.
In any case, the source code is available for those wishing to extend features. Additional information can be found at: http://www.math.aau.dk/~olefc/Programs/mcmcglmm/mcmcglmm.html
Morgan is a set of statistical tools for genetic Pedigree Analysis on observed data with possible epidemiological attributes. Utilities are available for addressing issues about pedigree structure, kinship and inbreeding coefficients, Monte Carlo and MCMC techniques for simulation of marker and trait data, estimating conditional gene ibd probabilities, LOD scores, parameter estimation and Polygenic Modeling of quantitative traits by EM algoritm.
Additional information may be found at: http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml
Radford Neal has contributed much over the years to Bayesian regression and classification theory and the areas of neural networks and machine learning. His FBM C based software routines provide modern methods in these areas and more. This software supports Bayesian regression and classification models based on neural networks and Gaussian processes, and Bayesian density estimation and clustering using mixture models and Dirichlet diffusion trees. It also supports a variety of Markov chain sampling methods, which may be applied to distributions specified by simple formulas, including simple Bayesian models defined by formulas for the prior and likelihood. For additional information check: http://www.cs.toronto.edu/~radford/fbm.software.html
University of Maryland Computer Science Dept. has developed two free graphical exploration tools for discovery of structure in multiple timeseries. Linkage, zooming, timebox queries, leaders, laggers and other capabilities are some of the features used in exploring structure in series. For more information: http://www.cs.umd.edu/hcil/timesearcher/
SatScan is a free software tool that analyzes spatial, temporal and space-time data using the spatial, temporal, or space-time scan statistics. The software may be useful in any area for which clustering in time and/or space needs to be identified. Circular and elliptical scan windows are provided as well as an user option to create elliptical window composites/mixtures. Likelihood ratio scan statistics are computed for a variety of statistical models and options for covariate adjustments are available. Additional info may be found at: http://www.satscan.org/
SABRE is a program created by the Center for Applied Statistics, Lancaster University, for the statistical analysis of multi-process random effect bivariate and trivariate response data. These responses can take the form of binary, ordinal, count and linear recurrent events in the clustered or longitudinal survey sampling settings. This is a fortran90 based code. Both serial and parallel versions are freely available. The parallel version may be of interest to those with large data sets. You may find out more at: