Search Results for "reliability"

...Designed for researchers, PhD scholars, professors, students, and analysts, it enables advanced quantitative research without subscriptions, cloud dependencies, or proprietary software restrictions. Key features include visual drag-and-drop model building, bootstrapping, mediation analysis, HTMT, AVE, Composite Reliability (CR), Cronbach's Alpha, model fit assessment, and Multi-Group Analysis (MGA). NAVAL-SEM also supports export to R, Python, and Lavaan for reproducible research workflows. Built for academic and professional research, NAVAL-SEM helps users conduct scale validation, measurement assessment, and structural modeling across disciplines including marketing, management, psychology, education, healthcare, and social sciences. ...

A brief summary of the main features of Fesslix: - Perform non-intrusive reliability analysis or Bayesian updating either --- by running commands on the command line or --- by means of an Octave interface or --- by means of a Python interface - Flexible input language for writing Fesslix parameter files --- Control flow statements (e.g. if, for, while) --- Most parameters can be defined as functions - Working with response surfaces - Linear finite element analysis using truss, beam and plane stress/strain elements - Spectral Stochastic Finite Elements - Bayesian networks This is the download page for Windows executables of Fesslix.

This is a small R package for doing Weibull-based reliability analysis. This R package is now obsolete and has been superseded by 'project Abernethy' on http://r-forge.r-project.org/projects/abernethy/.

Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes.

PYthon RELiabilitY A python package implementing state-of-the-art numerical methods arising in the field of uncertainty quantification : from statistical inference to uncertainty propagation for various purposes.