Open Source Statistics Software - Page 6

An R package implementation of a consensus clustering methodology. This package allows users to perform re-sampling statistics based clustering using multiple clustering algorithms to assess the robustness of both clusters and members of clusters.

An application to perform statistical clustering analysis

Development of exact and approximate methods (Importance Sampling and MCMC based) for computing likelihoods under the standard population genetic models of mutation,migration & recombination. Project issues are mainatined at https://freecode4susant.atlassian.net/browse/COALESCENT

CTSA is a C software package for univariate time series analysis. This is a work in progress. ARIMA and Seasonal ARIMA models have been added so far. Other functionality will be added soon . Documentation - https://github.com/rafat/ctsa/wiki

Shows the data density of a 2 dimensional distribution. The problem of showing data density visually is not mathematically well defined, and there are several methods. The program uses sum of reciprocal squared distance to calculate density at each point, with a smear factor to prevent points going to infinity. The smear factor also controls the amount of clustering. There are several options for colour output. Input is via a csv (comma-separated values) file. Now there's a nice GUI built in Baby X for Linux and Windows

The final build of this software now is distributed in R, embedded in "RedeR': an R/Bioconductor package for hierarchical and nested network analysis... more about RedeR: http://bioconductor.org/packages/2.9/bioc/html/RedeR.html

Moved to https://github.com/quansun/fantail-ml

A software framework to build maps for Neurospora crassa genome based on probabilistic models of meiotic recombination. A netbeans platform application is built to incorporate the computations. Project issues are mainatined at https://freecode4susant.atlassian.net/browse/GENOMEMAP

hSDM is an R package for hierarchical species distribution models. Such models allows interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results.

jAgg is a Java 5.0 API that supports “group by” operations on Lists of Java objects: aggregate operations such as count, sum, max, min, avg, and many more. It supports Super Aggregation: Rollups, Cube, and Grouping Sets. It supports analytic operations such as lag/lead and row number and more. It also allows custom aggregate and analytic operations.

Collection of several multi-purpose Java libraries. --- knowceans-tools = collection of Java utility classes. --- Highlights: --- org.knowceans.util: IndexQuickSort, TableList: apply order of one array/list to others +++ Vectors, ArrayUtils: array convenience +++ RandomSamplers, CokusRandom, ArmSampler, Densities: random sampling and distributions +++ Arguments: command line parser +++ StopWatch, Which, ExternalProcess: runtime stuff +++ ParallelFor: OpenMP workalike +++ PatternString, NamedGroupRegex: regex convenience --- org.knowceans.corpus: CorpusSearcher: full-text search engine +++ LabelNumCorpus: svmlight corpus storage and filtering +++ NIPS corpus with text, authors, labels and citations --- org.knowceans.map: InvertibleHashMultiMap, BijectiveHashMap: implement n:m and 1:1 relations. --- Other libs: knowceans-arms = port of the Adaptive Rejection Metropolis Sampler (ARMS) for arbitrary distributions +++ lda-j = port of lda-c, implementing Latent Dirichlet Allocation (LDA)

Mapgraph is SYSTAP’s disruptive new technology to exploit the main memory bandwidth advantages of GPUs. The early work was co-developed with the University of Utah SCI Institute and has its pedigree in the UINTAH software running on over 750M cores on the TITAN Super Computer. Today, SYSTAP has commercialized this technology into it’s Blazegraph Accelerator and Blazegraph HPC products. Checkout our options for GPU acceleration of graphs or contact us to learn more: https://www.blazegraph.com/product/gpu-accelerated/. The early work was released under the Apache 2 open source license and is available on here at Sourceforge. This work was (partially) funded by the DARPA XDATA program under AFRL Contract #FA8750-13-C-0002 and DARPA Contract #D14PC00029.

Tools to analyse and use passport data for biological collections.

Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.

An R package for metrology. metRology provides classes and calculation and plotting functions for metrology applications, including measurement uncertainty estimation and (eventually) inter-laboratory metrology comparison studies.

The minepy homepage has moved to http://minepy.readthedocs.io. The download page is now at https://github.com/minepy/minepy/releases.

This is a general project for modnlp/teccli plugins, with focus on text visualizaton.

Classic Texas Hold'Em Poker game in python.

phcfM is an R package for modelling anthropogenic deforestation. It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time.

O jogo consiste no seguinte: Monty Hall (o apresentador) apresentava 3 portas aos concorrentes, sabendo que atrás de uma delas está um carro (prémio bom) e que as outras têm prêmios de pouco valor. Na 1ª etapa o concorrente escolhe uma porta (que ainda não é aberta); De seguida Monty abre uma das outras duas portas que o concorrente não escolheu, sabendo à partida que o carro não se encontra aí; Agora com duas portas apenas para escolher — pois uma delas já se viu, na 2ª etapa, que não tinha o prêmio — e sabendo que o carro está atrás de uma delas, o concorrente tem que se decidir se permanece com a porta que escolheu no início do jogo e abre-a ou se muda para a outra porta que ainda está fechada para então a abrir. Qual é a estratégia mais lógica? Ficar com a porta escolhida inicialmente ou mudar de porta? Com qual das duas portas ainda fechadas o concorrente tem mais probabilidades de ganhar? Por quê?

Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.

Riboshape is a suite of algorithms to predict ribosome footprint profile shapes from transcript sequences. It applies kernel smoothing to codon sequences to build predictive features, and uses these features to builds a sparse regression model to predict the ribosome footprint profile shapes. Reference: Liu, T.-Y. and Song, Y.S. Prediction of ribosome footprint profile shapes from transcript sequences. Proceedings of ISMB 2016, Bioinformatics, Vol. 32 No. 12 (2016) i183-i191.

Builds synthetic data applicable across multiple domains. This package also provides flexibility to control data distribution to make it relevant to many industry examples.

This package provides high-level interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. A JAGS extension module provides additional distributions including the Pareto family of distributions, the DuMouchel prior and the half-Cauchy prior.