Search Results for "modelling"
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Showing 9 open source projects for "modelling"
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1
SCalc
Calculates the transportation cost seasonality indexes
Calculates the transportation cost seasonality indexes on the basis of the measurement approach by G. L. Lo Magno, M. Ferrante and S. De Cantis. -
2
ASEP simulation library
Simulation library for SSEP, ASEP or TASEP simulations
ASEP simulation library is specialized for simulations of Asymmetric Simple Exclusion Processes (ASEP) and its mutations like SSEP or TASEP based on a graph. It is consisted of agents, models, timers and graphs that forms united modelling enviroment ready for computer cluster use - all based on Zarja library. -
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hbgm
'Hierarchical Bond Graph Modelling of Biochemical Networks'
Scripts and supplementary data for the manuscript 'Hierarchical Bond Graph Modelling of Biochemical Networks': Peter J. Gawthrop(1), Joseph Cursons(1,2), and Edmund J. Crampin(1-4). (1) Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia. (2) ARC Centre of Excellence in Convergent Bio-Nano Science, Melbourne School of Engineering, University of Melbourne, Victoria 3010, Australia -
4
Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures,... -
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5
BiomeNet
BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES
...Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. ... -
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KeplerDB
Timeseries databases management system
...KeplerDB is dedicated to be scalable and to create clusters of server allowing the user to analyse and store massing amount of data to monitor systems like computers, clusters, building and captors or financial systems like markets and accounts. The user can use KeplerDB to make data analysis on enormous amount of data (statistics and modelling). -
7
phcfM
R package for modelling anthropogenic deforestation
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. ... -
8
FantasticLifeExpectancyCalculator
Calculate your and your spouse's life expectancy !
Using statistical modelling against raw data obtained from a USA Annuity mortality table, the Fantastic Life Expectancy Calculator allows users to input a number of parameters to determine their life expectancy. This calculator is provided free and for entertainment purposes only. It does not claim to accurately predict life expectancy for a specific individual or a specific couple. -
9
abc-sde
approximate Bayesian computation for stochastic differential equations
...It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/ -
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