Search Results for "logistic"

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

The new site is at http://psychometricon.net/libirt/ Library of functions to estimate the items and abilities from the responses of subjects to a questionnaire. The IRT models supported are the logistic model, the multivariate logistic model, the graded model and smoothing by penalization and kernel.

...The library contains the density (pdf), cumulative (cdf), quantile, and random number generator (RNG) routines of the following distributions: Ansari, Beta, Binomial, Cauchy, Chi square, Exponential, Fisher's F, Gamma, Geometric, Hypergeometric, Kendall, Logistic, Log normal, Negative binomial, Noncentral beta, Noncentral chi square, Noncentral f, Noncentral t, Normal, Poisson, Sign Rank, Spearman, Student's T, Tukey, Uniform, Weibull, Wilcoxon, and many more. Normality tests, such as: Kolmogorov-Smirnov, Anderson-Darling, Cramer-Von Mises, D'Agostino-Pearson, Jarque Bera, Kolmogorov-Lilliefors, Shapiro-Francia, Shapiro-Wilk. ...

This application supports the two process scientific and logistic . - register the demand for an analysis - register the targets, load in the database - obtain the best list of samples for those targets (the search can be made with different parameters) - be able to do it again till the list is not satisfied the statistician ( in term of analysis power ... ) - made the list in an excel spreadsheet - upload the list of the picked samples and upload the database - made the list for the laboratory which will made the technical parts

...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.

...Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a semi-supervised anomaly detection strategy based on logistic regression. Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl. ...

The objective of this project is to make available an open-source version of our Multifactor Dimensionality Reduction (MDR) software. MDR is a nonparametric alternative to logistic regression for detecting and characterizing nonlinear interactions.

DeDAY (Demography Data Analyses) is a tool of analyzing demography data. It supports Gompertz, Weibull and Logistic distributions. DeDay also supports mixed mortality models based on these distribution such as the Gompertz-Makeham distribution. Distributions such as Gompertz describes only age-dependent mortality, which increases over time. Mixed mortality models, such as in Gompertz-Makeham distribution, consider a more general case where mortality is consist of both age-dependent and in-dependent mortality. ...

LogiDist offer a solution of "Computer Aided Logistic" with mostly informative purposes on executed pickups/delivery of merchandise. Is able to manage the whole process of purchase, order management, merchandise delivery to reduce distribution costs.

Project is migrated to GitHub: https://github.com/OpenDAS OpenDAS is an "Open Data Acquisition System" and a new software aimed at industry use. This is the easiest software to acquire data for industry and logistic, above all, this is a universal software. Why universal?, because OpenDAS has been thought as a universal acquisition system. It can be used to acquire data for any software or any combination of softwares. You can use data that come from an HR system, send data to an ERP system. You can mix data coming from two softwares in order to use them in a unified business procedure Brought to you by ASPerience: http://www.asperience.fr/pole-applicatifs-metiers/saisie-industrielle