• Survey

  • Referenced in 52 articles [sw08163]
  • pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series ... linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. Predictive ... margins by direct standardization. PPS sampling without replacement. Principal components, factor analysis...
  • SMOTEBoost

  • Referenced in 35 articles [sw12571]
  • boosting algorithms give equal weight to all misclassified examples and sample from a pool ... class imbalance and to increase the sampling weights of minority class, SMOTE is introduced ... SMOTE increases the number of minority class samples for the learner and focus on these...
  • AIS-BN

  • Referenced in 25 articles [sw02223]
  • based on the theoretical properties of importance sampling in finite-dimensional integrals and the structural ... function, and (3) a dynamic weighting function for combining samples from different stages ... general purpose sampling algorithms, likelihood weighting and self-importance sampling. We used in our tests...
  • MWMOTE

  • Referenced in 14 articles [sw32596]
  • MWMOTE - Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning. Imbalanced learning problems contain ... unequal distribution of data samples among different classes and pose a challenge to any classifier ... learn informative minority class samples and assigns them weights according to their euclidean distance from ... then generates the synthetic samples from the weighted informative minority class samples using a clustering...
  • StreamKM++

  • Referenced in 14 articles [sw25552]
  • StreamKM++ computes a small weighted sample of the data stream,called the coreset ... significantly speed up the time necessary for sampling non-uniformly during the coreset construction. After ... extracted from the data stream, a weighted k-means algorithm is applied on the coreset...
  • PracTools

  • Referenced in 7 articles [sw28559]
  • package PracTools: Tools for Designing and Weighting Survey Samples. Functions and datasets to support Valliant ... Kreuter, “Practical Tools for Designing and Weighting Survey Samples” (2nd edition, 2018). Contains functions...
  • lavaan.survey

  • Referenced in 6 articles [sw11938]
  • complex sampling design. Incorporate clustering, stratification, sampling weights, and finite population corrections into...
  • hreg

  • Referenced in 15 articles [sw37389]
  • there is heteroscedasticity, clustered sampling, or the data is weighted...
  • MitISEM

  • Referenced in 4 articles [sw23111]
  • distribution is obtained using Importance Sampling weighted Expectation Maximization algorithm...
  • N-way Toolbox

  • Referenced in 30 articles [sw12996]
  • weighted least squares loss function (including MILES); Predicting scores for new samples using a given...
  • loo

  • Referenced in 20 articles [sw19420]
  • Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct...
  • parallelMCMCcombine

  • Referenced in 3 articles [sw21115]
  • this package, including averaging across subset samples, weighted averaging across subsets samples, and kernel smoothing...
  • ROAST

  • Referenced in 7 articles [sw17318]
  • number of rotations does not depend on sample size, ROAST gives useful results even ... also incorporate array weights and correlated samples. ROAST can be tuned for situations in which ... direction regulation. Probes can also be weighted to allow for prior importance. The power...
  • MentorNet

  • Referenced in 3 articles [sw42304]
  • During training, MentorNet provides a curriculum (sample weighting scheme) for StudentNet to focus...
  • hitandrun

  • Referenced in 4 articles [sw21592]
  • such shapes. Includes specialized functions for sampling normalized weights with arbitrary linear constraints...
  • WeightedPortTest

  • Referenced in 13 articles [sw12429]
  • resulting statistics are weighted sums of the squares of the sample autocorrelation coefficients that, unlike...
  • optweight

  • Referenced in 2 articles [sw35699]
  • Weights Using Optimization. Use optimization to estimate weights that balance covariates for binary, multinomial ... specified for each covariate. In addition, sampling weights can be estimated that allow a sample...
  • rsw

  • Referenced in 1 article [sw40811]
  • Optimal representative sample weighting (rsw) in Python. This package implements the methods described ... paper Optimal Representative Sample Weighting. At a high level, the package takes in a dataset ... nonnegative weight, so as to make weighted sample averages equal or close to some desired...
  • WGCNA

  • Referenced in 26 articles [sw07123]
  • Correlation Network Analysis. Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data ... relating of variables and modules to sample traits. Also includes a number of utility functions...
  • PROC SURVEYFREQ

  • Referenced in 1 article [sw40487]
  • design. The WEIGHT statement names the sampling weight variable. The REPWEIGHTS statement names replicate weight...