- Referenced in 1567 articles
- Elements of Statistical Learning, Data Mining, Inference, and Prediction” by Trevor Hastie, Robert Tibshirani...
- Referenced in 338 articles
- complex hierarchical models, in which statistical inference is only possible using Markov Chain Monte Carlo ... construct fast and reliable algorithms for MCMC inference, and provide an online C-library ... ecology, introducing them to this powerful statistical inference method...
- Referenced in 490 articles
- expressive programming model and successful type inference, leading to good performance for a wide range...
- Referenced in 285 articles
- ANFIS: adaptive-network-based fuzzy inference system. The architecture and learning procedure underlying ANFIS (adaptive ... network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented...
- Referenced in 382 articles
- BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian...
- Referenced in 320 articles
- first-order logic with equality. Otter’s inference rules are based on resolution and paramodulation...
- Referenced in 310 articles
- system can be extended with new inference rules without compromising soundness. While retaining this reliability...
- Referenced in 302 articles
- probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized...
- Referenced in 276 articles
- sound, polymorphic type system featuring type inference. The OCaml system is an industrial-strength implementation...
- Referenced in 161 articles
- ETPS issues commands to apply rules of inference in specified ways, and the computer handles ... formulas from them. The rules of inference and predefined problems in ETPS are mostly taken ... Publishers, 2002. Descriptions of the rules of inference are available online. When the teacher permits...
- Referenced in 143 articles
- simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment ... simulated automatically. Also provides facilities for formal inference (such as chi-squared tests) and model...
- Referenced in 117 articles
- high-level programming language combining constraint inference with concurrency. Typical application areas of Oz include ... powerful primitives for programming constraint inference engines at a high level...
- Referenced in 162 articles
- package quantreg: Quantile Regression. Estimation and inference methods for models of conditional quantiles: Linear...
- Referenced in 99 articles
- weak learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm ... likelihood. This approach enables full posterior inference including point and interval estimates of the unknown...
- Referenced in 134 articles
- summarizes some recent work on causal inference, relevant when graphical models are given a causal...
- Referenced in 92 articles
- package pcalg: Estimation of CPDAG/PAG and causal inference using the IDA algorithm , Standard and robust ... available for estimating PAGs. Functions for causal inference using the IDA algorithm (based...
- Referenced in 78 articles
- Bayesian network structure learning, parameter learning and inference. Bayesian network structure learning, parameter learning ... inference. This package implements constraint-based (GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton ... parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries and cross-validation. Development...
Fuzzy Logic Toolbox
- Referenced in 72 articles
- through the steps of designing fuzzy inference systems. Functions are provided for many common methods ... then implement these rules in a fuzzy inference system ... stand-alone fuzzy inference engine. Alternatively, you can use fuzzy inference blocks in Simulink...
- Referenced in 122 articles
- programming language LOP (under development). The inference machine of the system is implemented using Prolog...
- Referenced in 87 articles
- programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian ... inference via variational approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three...