Search Results for "u-root"

Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. ...

Diagonal can be used for: - getting descriptive statistics such as mean/median/mode with your program producing a sample - finding a root of an equation your program defines - calculating a fixed point of a function your program defines - detecting a cycle of a fuction your program defines as well as - decoding a VCDIFF file

I Ching offers an idea to summary the world by constructing functional mappings in finite groups. Much of ancient Chinese natural and social science grew from its concepts as root. The derived theories like "Eight Diagrams", "Five Elements" became the foundation of nearly all academic fields in acient Chinese. As a result, the theories are also the high concentration of many practical and statistical experience in China during her thousands-of-year history. This project tries to realize these algorithms with statistical programming. ...

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide...

...Features: - Capable of high order factorial designs (> 2 factors) - Within and mixed analyses of variance provide corrections for violations of sphericity (Huynh-Feldt, Greenhouse-Geisser, Box) - A variety of data transformations can be applied (log10, reciprocal, arcsine, square-root, and Windsor) - Generalized eta-squared measures of effect size - Post-hoc power analysis (should match G*Power) - Outputs include tables of estimated marginal means - Up to 4-way interaction plots with errorbars (png, svg) - Confidence intervals account for within-subject variability (where applicable; Loftus and Masson, 1994) - Non-proprietary HTML output files - Non-proprietary codebase Gotchas: - Assumes balanced designs

Statastizard(c)2012 Nick Emblow is a program designed to guide its user into the right statistical test, perform the test, and report the results in a meaningful way. The idea of this is that the user won't actually need to know that they are using a mann-whitney U over a t-test, for example - it just tests for normality and homoscedastic of variance, and decides which test to use, then reports the results. Why? Because time after time, people come to me with some test that they've done that they think "proves" something - when in reality they've either not done a comparative test to start with (ex. a correlation), failed to test for confounding factors (such as normality etc) and as a result, failed to appropriately identify even the right test to do.