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  • fda (R)
  • Referenced in 1312 articles [sw04511]
  • functional data analysis functions and sample analyses through the CRAN distribution system. This ... files containing the functions and sample analyses, as well as two .txt files giving instructions...

  • TSPLIB
  • Referenced in 661 articles [sw00983]
  • TSPLIB is a library of sample instances for the TSP (and related problem) from various...

  • TETRAD
  • Referenced in 386 articles [sw12177]
  • about the true structure in the large sample limit, provided that structure and the sample...

  • CoSaMP
  • Referenced in 202 articles [sw08727]
  • Iterative signal recovery from incomplete and inaccurate samples. Compressive sampling offers a new paradigm ... basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from ... noisy samples. This paper describes a new iterative recovery algorithm called CoSaMP that delivers ... requires only matrix-vector multiplies with the sampling matrix. For compressible signals, the running time...

  • BUGS
  • Referenced in 358 articles [sw07885]
  • BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian...

  • EGO
  • Referenced in 335 articles [sw07588]
  • surface and improving the approximation by sampling where the prediction error may be high...

  • gss
  • Referenced in 273 articles [sw06099]
  • conditional density estimation under a variety of sampling schemes; and (iii) hazard rate estimation with...

  • NewtonLib
  • Referenced in 265 articles [sw04796]
  • intended usage. Please read our sample license agreement (or the german version) for more details...

  • SMOTE
  • Referenced in 125 articles [sw34239]
  • SMOTE: Synthetic Minority Over-sampling Technique. An approach to the construction of classifiers from imbalanced ... cost of the reverse error. Under-sampling of the majority (normal) class has been proposed ... combination of our method of over-sampling the minority (abnormal) class and under-sampling ... performance (in ROC space) than only under-sampling the majority class. This paper also shows...

  • Stan
  • Referenced in 167 articles [sw10200]
  • Stan: A C++ Library for Probability and Sampling. Stan is a probabilistic programming language implementing ... full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood estimation with...

  • Bertini
  • Referenced in 220 articles [sw06683]
  • Allows for witness set manipulation via both sampling and membership testing. Accepts square or nonsquare...

  • MEMSS
  • Referenced in 186 articles [sw11219]
  • effects Models in S .Data sets and sample analyses from Pinheiro and Bates, ”Mixed-effects...

  • Cayley
  • Referenced in 130 articles [sw01053]
  • some of the algorithms it incorporates. Four sample CAYLEY programs are given: a test ... easy and comfortable to use. As the sample programs show, novel approaches may be needed...

  • C-XSC 2.0
  • Referenced in 123 articles [sw00182]
  • have to be done. Note, that all sample codes given in [R. Klatte ... work properly with C-XSC 2.0. Sample codes are available on the web page...

  • survival
  • Referenced in 155 articles [sw04364]
  • penalised likelihood , survival analysis: descriptive statistics, two-sample tests, parametric accelerated failure models, Cox model...

  • CMA-ES
  • Referenced in 102 articles [sw05063]
  • evolution strategy, new candidate solutions are sampled according to a multivariate normal distribution ... candidate solutions is exploited for learning the sample distribution and neither derivatives nor even...

  • copula

  • Referenced in 132 articles [sw14499]
  • package ’nacopula’ for nested Archimedean copulas: Efficient sampling algorithms, various estimators, goodness-of-fit tests...

  • spatstat
  • Referenced in 128 articles [sw04429]
  • exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types...

  • TOMS659
  • Referenced in 128 articles [sw10686]
  • because low discrepancy sequences tend to sample space ”more uniformly” than random numbers. Algorithms that...

  • cmprsk
  • Referenced in 123 articles [sw11073]
  • Gray (1988), A class of K-sample tests for comparing the cumulative incidence...