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R: Shrinkage-mean-based Diagonal Quadratic Discriminant Analysis...
...Discriminant Analysis (SmDQDA) from Tong, Chen, and Zhao (2012) Description Given a set of training data, this function builds the Shrinkage-mean-based Diagonal Quadratic Discriminant Analysis (SmDQDA)...
/CRAN/refmans/sparsediscrim/html/qda_shrink_mean.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Diagonal Linear Discriminant Analysis.
Dlda {HiDimDA} R Documentation Diagonal Linear Discriminant Analysis. Description ‘Dlda’ finds the coefficients of a linear discriminant rule based on a Diagonal covariance matrix estimator.
/CRAN/refmans/HiDimDA/html/Dlda.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Shrinkage-mean-based Diagonal Linear Discriminant Analysis...
...Diagonal Linear Discriminant Analysis (SmDLDA) from Tong, Chen, and Zhao (2012) Description Given a set of training data, this function builds the Shrinkage-mean-based Diagonal Linear Discriminant...
/CRAN/refmans/sparsediscrim/html/lda_shrink_mean.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Shrinkage-based Diagonal Quadratic Discriminant Analysis...
...Shrinkage-based Diagonal Quadratic Discriminant Analysis (SDQDA) Description Given a set of training data, this function builds the Shrinkage-based Diagonal Quadratic Discriminant Analysis (SDQDA)...
/CRAN/refmans/sparsediscrim/html/qda_shrink_cov.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Shrinkage-based Diagonal Linear Discriminant Analysis (SDLDA)
...Shrinkage-based Diagonal Linear Discriminant Analysis (SDLDA) Description Given a set of training data, this function builds the Shrinkage-based Diagonal Linear Discriminant Analysis (SDLDA)...
/CRAN/refmans/sparsediscrim/html/lda_shrink_cov.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Diagonal Quadratic Discriminant Analysis (DQDA)
...Diagonal Quadratic Discriminant Analysis (DQDA) Description Given a set of training data, this function builds the Diagonal Quadratic Discriminant Analysis (DQDA) classifier, which is often attributed...
/CRAN/refmans/sparsediscrim/html/qda_diag.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Diagonal Linear Discriminant Analysis (DLDA)
...Diagonal Linear Discriminant Analysis (DLDA) Description Given a set of training data, this function builds the Diagonal Linear Discriminant Analysis (DLDA) classifier, which is often attributed...
/CRAN/refmans/sparsediscrim/html/lda_diag.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Diagonal Discriminant Analysis
...Diagonal Discriminant Analysis Description This function implements a simple Gaussian maximum likelihood discriminant rule, for diagonal class covariance matrices. In machine learning lingo, this...
/CRAN/refmans/sfsmisc/html/diagDA.html
cran-help matching:
diagonal, diagonal, discriminant, discriminant, analysis and analysis |
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R: Sparse and Regularized Discriminant Analysis
Sparse and Regularized Discriminant Analysis Documentation for package ‘sparsediscrim’ version 0.3.0 DESCRIPTION file. Package NEWS. Help Pages center_data Centers the observations in a matrix by...
/CRAN/refmans/sparsediscrim/html/00Index.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Linear discriminant analysis via regularization
...Linear discriminant analysis via regularization Description Functions in the sparsediscrim package fit different types of linear discriminant analysis model that regularize the estimates (like...
/CRAN/refmans/parsnip/html/details_discrim_linear_sparsediscrim.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Quadratic discriminant analysis via regularization
...Quadratic discriminant analysis via regularization Description Functions in the sparsediscrim package fit different types of quadratic discriminant analysis model that regularize the estimates (like...
/CRAN/refmans/parsnip/html/details_discrim_quad_sparsediscrim.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Linear discriminant analysis via James-Stein-type shrinkage...
...James-Stein-type shrinkage estimation Description sda::sda() can fit a linear discriminant analysis model that can fit models between classical discriminant analysis and diagonal discriminant analysis.
/CRAN/refmans/parsnip/html/details_discrim_linear_sda.html
cran-help matching:
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R: Regularised discriminant analysis for Euclidean data
...discriminant analysis for Euclidean data {regda} R Documentation Regularised discriminant analysis for Euclidean data Description Regularised discriminant analysis for Euclidean data. Usage rda(xnew...
/CRAN/refmans/regda/html/rda.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: High Dimensional Discriminant Analysis
...A C D F H I L M P R S misc HiDimDA-package High Dimensional Discriminant Analysis -- A -- AlonDS Alon Colon Cancer Data Set as.matrix.DMat DMat objects: diagonal matrices as.matrix.ShrnkMat ShrnkMat...
/CRAN/refmans/HiDimDA/html/00Index.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Barycentric Discriminant Analysis
...Discriminant Analysis Description Barycentric Discriminant Analysis (BADA) via TExPosition. Usage tepBADA(DATA, scale = TRUE, center = TRUE, DESIGN = NULL, make_design_nominal = TRUE, group.masses...
/CRAN/refmans/TExPosition/html/tepBADA.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Regularised and flexible discriminant analysis for...
...Regularised and flexible discriminant analysis for compositional data using the \alpha-transformation Description Regularised and flexible discriminant analysis for compositional data using the \alpha-...
/CRAN/refmans/Compositional/html/alfa.rda.html
cran-help matching:
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R: Discriminant Correspondence Analysis
...Discriminant Correspondence Analysis Description Discriminant Correspondence Analysis (DICA) via TExPosition. Usage tepDICA(DATA, make_data_nominal = FALSE, DESIGN = NULL, make_design_nominal = TRUE...
/CRAN/refmans/TExPosition/html/tepDICA.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Linear Discriminant Analysis using the Generalized Singular...
...both predictors and the response. Missing values are NOT allowed. Details Traditional Fisher's Linear Discriminant Analysis (LDA) ceases to work when the within-class scatter matrix is singular.
/CRAN/refmans/LDATree/html/ldaGSVD.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Binary Discriminant Analysis: Model Fit and Class Prediction
...Discriminant Analysis: Model Fit and Class Prediction Description binda trains a diagonal multivariate Bernoulli model. predict.binda performs corresponding class prediction. Usage binda(Xtrain, L...
/CRAN/refmans/binda/html/binda.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: High Dimensional Discriminant Analysis
...Dimensional Discriminant Analysis Description Performs Linear Discriminant Analysis in High Dimensional problems based on reliable covariance estimators for problems with (many) more variables than...
/CRAN/refmans/HiDimDA/html/HiDimDA-package.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Shrunken Linear Discriminant Analysis.
...Discriminant Analysis. Description ‘Slda’ finds the coefficients of a linear discriminant rule based on Fisher and Sun's (2011) estimate and generalizations of Ledoit and Wolf's (2004) optimal...
/CRAN/refmans/HiDimDA/html/Slda.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Heteroscedastic discriminant analysis
...Heteroscedastic discriminant analysis Description Computes a linear transformation loadings matrix for discrimination of classes with unequal covariance matrices. Usage hda(x, ...) ## Default S3...
/CRAN/refmans/hda/html/hda.html
cran-help matching:
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R: Shrinkage Discriminant Analysis 2: Training Step
...Discriminant Analysis 2: Training Step Description sda trains a LDA or DDA classifier using James-Stein-type shrinkage estimation. Usage sda(Xtrain, L, lambda, lambda.var, lambda.freqs, diagonal=FALSE...
/CRAN/refmans/sda/html/sda.html
cran-help matching:
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R: Quadratic discriminant analysis
...Quadratic discriminant analysis Description discrim_quad() defines a model that estimates a multivariate distribution for the predictors separately for the data in each class (usually Gaussian...
/CRAN/refmans/parsnip/html/discrim_quad.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Linear discriminant analysis
...Linear discriminant analysis Description discrim_linear() defines a model that estimates a multivariate distribution for the predictors separately for the data in each class (usually Gaussian...
/CRAN/refmans/parsnip/html/discrim_linear.html
cran-help matching:
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R: Factor Adjusted Discriminant Analysis 3-4 : Supervised...
...Discriminant Analysis 3-4 : Supervised classification on decorrelated data Description This function performs supervised classification on factor-adjusted data. Usage FADA(faobject, K=10,B=20, nbf.cv...
/CRAN/refmans/FADA/html/FADA.html
cran-help matching:
diagonal, discriminant, discriminant, analysis and analysis |
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R: Regularized Discriminant Analysis (RDA)
...Regularized Discriminant Analysis (RDA) Description Builds a classification rule using regularized group covariance matrices that are supposed to be more robust against multicollinearity in the...
/CRAN/refmans/klaR/html/rda.html
cran-help matching:
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R: Tuning the parameters of the regularised discriminant...
...discriminant analysis {regda} R Documentation Tuning the parameters of the regularised discriminant analysis Description Tuning the parameters of the regularised discriminant analysis for Eucldiean...
/CRAN/refmans/regda/html/rda.tune.html
cran-help matching:
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R: Kernel discriminant analysis (kernel classification)
...discriminant analysis (kernel classification) Description Kernel discriminant analysis (kernel classification) for 1- to d-dimensional data. Usage kda(x, x.group, Hs, hs, prior.prob=NULL, gridsize...
/CRAN/refmans/ks/html/kda.html
cran-help matching:
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R: Shrinkage Discriminant Analysis 1: Predictor Ranking
...Discriminant Analysis 1: Predictor Ranking Description sda.ranking determines a ranking of predictors by computing CAT scores (correlation-adjusted t-scores) between the group centroids and the pooled...
/CRAN/refmans/sda/html/sda.ranking.html
cran-help matching:
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R: Fits a regularization path of Sparse Discriminant Analysis...
msda {TULIP} R Documentation Fits a regularization path of Sparse Discriminant Analysis and predicts Description Fits a regularization path of Sparse Discriminant Analysis at a sequence...
/CRAN/refmans/TULIP/html/msda.html
cran-help matching:
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R: Computes estimates and ancillary information for diagonal...
diag_estimates {sparsediscrim} R Documentation Computes estimates and ancillary information for diagonal classifiers Description Computes the maximum likelihood estimators (MLEs) for each class under...
/CRAN/refmans/sparsediscrim/html/diag_estimates.html
cran-help matching:
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R: Sex discrimination in Employment
...discrimination in Employment Description Data on employees from one job category (skilled, entry–level clerical) of a bank that was sued for sex discrimination. The data are on 32 male and 61 female...
/CRAN/refmans/Sleuth3/html/case1202.html
cran-help matching:
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R: Canonical Analysis of Principal Coordinates based on...
...Canonical Analysis of Principal Coordinates based on Discriminant Analysis Description This function provides a method for CAP that follows the procedure as described by the authors of the ordination...
/CRAN/refmans/BiodiversityR/html/CAPdiscrim.html
cran-help matching:
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R: An R6 Class to represent a PLNfit in a LDA framework with...
...PLNfit in a LDA framework with diagonal covariance Description The function PLNLDA() produces an instance of an object with class PLNLDAfit. This class comes with a set of methods, some of them being...
/CRAN/refmans/PLNmodels/html/PLNLDAfit_diagonal.html
cran-help matching:
diagonal, diagonal, discriminant and analysis |
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R: Variable selection for supervised classification in high...
...the FADA (Factor Adjusted Discriminant Analysis) package aim at performing supervised classification of high-dimensional and correlated profiles. The procedure combines a decorrelation step based on...
/CRAN/refmans/FADA/html/FADA-package.html
cran-help matching:
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R: An R6 Class to represent a PLNfit in a standard, general...
...framework, with diagonal residual covariance Description The function PLNLDA() produces an instance of an object with class PLNLDAfit. This class comes with a set of methods, some of them being useful...
/CRAN/refmans/PLNmodels/html/PLNfit_diagonal.html
cran-help matching:
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R: Tong et al. (2012)'s Lindley-type Shrunken Mean Estimator
...utilized in shrinkage-mean-based diagonal linear discriminant analysis (SmDLDA). Usage tong_mean_shrinkage(x, r_opt = NULL) Arguments x a matrix with n rows and p columns. r_opt the shrinkage...
/CRAN/refmans/sparsediscrim/html/tong_mean_shrinkage.html
cran-help matching:
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R: Principal Tensor Analysis on 3 modes
...Analysis on 3 modes Description Performs a truncated SVD-3modes analysis with or without specific metrics, penalised or not. Usage PTA3(X,nbPT=2,nbPT2=1, smoothing=FALSE, smoo=list(function(u)ksmooth...
/CRAN/refmans/PTAk/html/PTA3.html
cran-help matching:
diagonal, discriminant, analysis and analysis |
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R: iclust: Item Cluster Analysis - Hierarchical cluster analysis...
...iclust: Item Cluster Analysis – Hierarchical cluster analysis using psychometric principles Description A common data reduction technique is to cluster cases (subjects). Less common, but...
/CRAN/refmans/psych/html/ICLUST.html
cran-help matching:
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R: Classification with Wilma's Clusters
...Wilma's Clusters Description The four functions nnr (nearest neighbor rule), dlda (diagonal linear discriminant analysis), logreg (logistic regression) and aggtrees (aggregated trees) are used for...
/CRAN/refmans/supclust/html/dlda.html
cran-help matching:
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R: The sda Package
...performs linear discriminant analysis (LDA) and diagonal discriminant analysis (DDA) with variable selection using correlation-adjusted t (CAT) scores. The classifier is trained using James-Stein-type...
/CRAN/refmans/sda/html/sda.package.html
cran-help matching:
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R: Principal Tensor Analysis on k modes
...Tensor Analysis on k modes Description Performs a truncated SVD-kmodes analysis with or without specific metrics, penalised or not. Usage PTAk(X,nbPT=2,nbPT2=1,minpct=0.1, smoothing=FALSE, smoo=list...
/CRAN/refmans/PTAk/html/PTAk.html
cran-help matching:
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R: Utilities from 'Seminar fuer Statistik' ETH Zurich
...integer.basedInt Digit/Bit Representation of Integers in any Base AsciiToInt Character to and from Integer Codes Conversion axTexpr Axis Ticks Expressions in Nice 10 ** k Form -- B -- bi2int Digit/Bit ...
/CRAN/refmans/sfsmisc/html/00Index.html
cran-help matching:
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R: Function to learn a binary classification rule
...two class, use learnPartitionWithLLR instead. The learned rule can be linear or quadratic. There are reduction dimension methods (accessible via argument procedure) to make the procedure efficient...
/CRAN/refmans/VHDClassification/html/learnBinaryRule.html
cran-help matching:
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R: 3-D Reduced Rank Regression Plots
...three-dimensional, interactive plotly graphics for exploration and diagnostics. Usage threewise_plot(x, y, type = "pca", pair_x = 1, pair_y = 2, pair_z = 3, rank = "full", k = 0, point_size = 2.5)...
/CRAN/refmans/rrr/html/threewise_plot.html
cran-help matching:
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R: Predict Method for Wilma
...on the supervised gene clusters wilma found, and on a choice of four different classifiers: the nearest-neighbor rule, diagonal linear discriminant analysis, logistic regression and aggregated trees.
/CRAN/refmans/supclust/html/predict.wilma.html
cran-help matching:
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R: Sparse Matrix Estimation and Inference
...two main functions used to estimate the covariance matrix and the precision matrix of the data under the assumption of sparsity, that most off-diagonal entries are zero. This is achieved by selecting...
/CRAN/refmans/sparseMatEst/html/sparseMatEst-package.html
cran-help matching:
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R: Create an instance of the ['GaussianModel'] class
...defining a family of models. "general" for the general family, "diagonal" for the diagonal family, "spherical" for the spherical family and "all" for all families. Default is "general". listModels a...
/CRAN/refmans/Rmixmod/html/mixmodGaussianModel.html
cran-help matching:
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R: Compute Latent Variable Scores
type = "identity", the default, uses \mathbf{\Gamma} = \mathbf{I} to fit a reduced-rank regression. type = "pca" fits a principal component analysis model as a special case of reduced-rank regression.
/CRAN/refmans/rrr/html/scores.html
cran-help matching:
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R: Cross validation for the regularised and flexible...
...for the regularised and flexible discriminant analysis with compositional data using the \alpha-transformation Description Cross validation for the regularised and flexible discriminant analysis...
/CRAN/refmans/Compositional/html/alfarda.tune.html
cran-help matching:
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R: Confusion Matrix
...compute the confusion matrix of two classification vectors. It can be useful for evaluating discriminant analysis or other classification systems. Usage confusionmatrix(obs, predict) Arguments obs a...
/CRAN/refmans/biotools/html/confusionmatrix.html
cran-help matching:
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R: Reduced-Rank Regression Residuals
...residuals calculates the regression residuals for reduced-rank regression and canonical variate analysis. Usage residuals(x, y, type = "identity", rank = "full", k = 0, plot = TRUE) Arguments x...
/CRAN/refmans/rrr/html/residuals.html
cran-help matching:
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R: Bias correction function from Pang et al. (2009).
...h_{\nu, p}(t) on page 1023 of Pang et al. (2009). Usage h(nu, p, t = -1) Arguments nu a specified constant (nu = N - K) p the feature space dimension. t a constant specified by the user that indicates...
/CRAN/refmans/sparsediscrim/html/h.html
cran-help matching:
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R: A Collection of Efficient and Extremely Fast R Functions II
...‘Rfast2’ version 0.1.5.2 DESCRIPTION file. Package NEWS. Help Pages A B C D E F G H I J K L M N O P Q R S T U V W Z Rfast2-package Really fast R functions -- A -- add.term Add many single terms...
/CRAN/refmans/Rfast2/html/00Index.html
cran-help matching:
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R: Confer inertia to factors of a 'tbl_ord' object
...Re-distribute inertia between rows and columns in an ordination. Usage recover_conference(x) ## Default S3 method: recover_conference(x) get_conference(x) revert_conference(x) confer_inertia(x, p)...
/CRAN/refmans/ordr/html/conference.html
cran-help matching:
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R: Fit Reduced-Rank Regression Model
...to fit. type = "identity", the default, uses \mathbf{\Gamma} = \mathbf{I} to fit a reduced-rank regression. type = "pca" fits a principal component analysis model as a special case of reduced-rank ...
/CRAN/refmans/rrr/html/rrr.html
cran-help matching:
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R: Pairwise Plots
...type of reduced-rank regression model to fit. type = "identity", the default, uses \mathbf{\Gamma} = \mathbf{I} to fit a reduced-rank regression. type = "pca" fits a principal component analysis model ...
/CRAN/refmans/rrr/html/pairwise_plot.html
cran-help matching:
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R: Principal components analysis (PCA)
...Does an eigen value decomposition and returns eigen values, loadings, and degree of fit for a specified number of components. Basically it is just doing a principal components analysis (PCA) for n...
/CRAN/refmans/psych/html/principal.html
cran-help matching:
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R: Rank Trace Plot
rank_trace {rrr} R Documentation Rank Trace Plot Description rank_trace is a plot used to determine the effective dimensionality, i.e., t = \mathrm{rank}\left(\mathbf{C}\right), of the reduced-rank...
/CRAN/refmans/rrr/html/rank_trace.html
cran-help matching:
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R: Default conjugate prior for Gaussian mixtures
defaultPrior {mclust} R Documentation Default conjugate prior for Gaussian mixtures Description Default conjugate prior specification for Gaussian mixtures. Usage defaultPrior(data, G, modelName...
/CRAN/refmans/mclust/html/defaultPrior.html
cran-help matching:
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R: Shrinkage-based estimator of variances for each feature from...
...feature (variable) from Pang et al. (2009) for the SDLDA classifier. Usage var_shrinkage(N, K, var_feature, num_alphas = 101, t = -1) Arguments N the sample size. K the number of classes. var_feature...
/CRAN/refmans/sparsediscrim/html/var_shrinkage.html
cran-help matching:
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R: *ordr* package
...ordination analysis and biplot visualization into a tidyverse workflow. It is inspired in particular by the extensions ggbiplot and tidygraph. The package consists in several modules: the 'tbl_ord'...
/CRAN/refmans/ordr/html/ordr.html
cran-help matching:
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R: A List of Available Models in train
...fastAdaboost with tuning parameters: Number of Trees (nIter, numeric) Method (method, character) AdaBoost.M1 (method = 'AdaBoost.M1') For classification using packages adabag and plyr with tuning...
/CRAN/refmans/caret/html/models.html
cran-help matching:
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R: Kernel bandwidth estimators for hypervolumes
...{hypervolume} R Documentation Kernel bandwidth estimators for hypervolumes Description Estimates bandwidth vector from data using multiple approaches. Usage estimate_bandwidth(data,method="silverman"...
/CRAN/refmans/hypervolume/html/estimate_bandwidth.html
cran-help matching:
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R: Stein Risk function from Pang et al. (2009).
...for \alpha \in [0,1] that empirically minimizes the average risk under a Stein loss function, which is given on page 1023 of Pang et al. (2009). Usage risk_stein(N, K, var_feature, num_alphas = 101, t...
/CRAN/refmans/sparsediscrim/html/risk_stein.html
cran-help matching:
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R: Plotting functions for the psych package of class "psych"
...'psych' plot(x,labels=NULL,...) ## S3 method for class 'irt' plot(x,xlab,ylab,main,D,type=c("ICC","IIC","test"),cut=.3,labels=NULL, keys=NULL, xlim,ylim,y2lab,lncol="black",...) ## S3 method for class ...
/CRAN/refmans/psych/html/plot.psych.html
cran-help matching:
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R: Log Density for Gaussian Mixture Model
...the log density for observations in a univariate or multivariate Gaussian mixture model with spherical or diagonal (co)variance that varies across components. Usage logdens( x, simData, shrink = 1)...
/CRAN/refmans/probout/html/logdens.html
cran-help matching:
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R: Fits a regularization path for Multi-Class Sparse...
...Multi-Class Sparse Discriminant Analysis Description Fits a regularization path for Multi-Class Sparse Discriminant Analysis at a sequence of regularization parameters lambda. Usage msda(x, y, nlambda...
/CRAN/refmans/msda/html/msda.html
cran-help matching:
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R: Spectral Graph Clustering
...Use spectral embedding to embed a graph into a lower dimension, then cluster the points using model based clustering. This results in a clustering of the vertices. Usage cluster_spectral(g, verbose...
/CRAN/refmans/HyperG/html/cluster_spectral.html
cran-help matching:
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R: Summarizing distance-based partial least squares fits
...methods to the low level. Value A list of class summary.dbplsr containing the following components: ncomp the number of components of the model. r.squared the coefficient of determination R2. adj...
/CRAN/refmans/dbstats/html/summary.dbplsr.html
cran-help matching:
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R: Summarizing distance-based linear model fits
...dblm. Result of dblm. ... arguments passed to or from other methods to the low level. Value A list of class summary.dblm containing the following components: residuals the residuals (response minus...
/CRAN/refmans/dbstats/html/summary.dblm.html
cran-help matching:
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R: Create an instance of the ['CompositeModel'] class
...{Rmixmod} R Documentation Create an instance of the [CompositeModel] class Description Define a list of heterogeneous model to test in MIXMOD. Usage mixmodCompositeModel( listModels = NULL, free...
/CRAN/refmans/Rmixmod/html/mixmodCompositeModel.html
cran-help matching:
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R: Summarizing distance-based generalized linear model fits
...dbglm {dbstats} R Documentation Summarizing distance-based generalized linear model fits Description summary method for class "dbglm" Usage ## S3 method for class 'dbglm' summary(object,dispersion...
/CRAN/refmans/dbstats/html/summary.dbglm.html
cran-help matching:
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R: Compute the area under the ROC curve
auc {pROC} R Documentation Compute the area under the ROC curve Description This function computes the numeric value of area under the ROC curve (AUC) with the trapezoidal rule. Two syntaxes are...
/CRAN/refmans/pROC/html/auc.html
cran-help matching:
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R: Poisson Lognormal Models
...by 'PLNLDA()' coef.PLNmixturefit Extract model coefficients coef.ZIPLNfit Extract model coefficients coefficient_path Extract the regularization path of a PLNnetwork fit compute_offset Compute ...
/CRAN/refmans/PLNmodels/html/00Index.html
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R: SVD with metrics and smoothing approximation
...asked to constraint the components (u and v) to be smooth. Usage SVDgen(Y, D2 = 1, D1 = 1, smoothing = FALSE, nomb = NULL, smoo = list(function(u)ksmooth( 1:length(u), u, kernel = "normal", bandwidth...
/CRAN/refmans/PTAk/html/SVDgen.html
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R: Main Function For Fechnerian Scaling
...For Fechnerian Scaling Description fechner provides the Fechnerian scaling computations. It is the main function of this package. Usage fechner(X, format = c("probability.different", "percent.same"...
/CRAN/refmans/fechner/html/fechner.html
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R: Sparse Generalized Eigenvalue Problem
...Optimal Statistical Rates via Truncated Rayleigh Flow", by Tan et al. (2018). The main functions are as follows: (1) initial.convex (2) rifle The first function, initial.convex, solves the sparse...
/CRAN/refmans/rifle/html/rifle-package.html
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R: Q-Kernel-Based and Conditionally Negative Definite Kernel-Based Machine Learning Tools
...NEWS. Help Pages A B C D E F I K L M N P Q R S T W X Y -- A -- anocnd CND Kernel Functions anokernel-class Class "cndkernel" "nonlkernel" "polykernel" "rbfkernel" "laplkernel" as.cndkernmatrix Assing...
/CRAN/refmans/qkerntool/html/00Index.html
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R: Markov Chain Monte Carlo for K-Dimensional Item Response...
...distribution of a K-dimensional item response theory (IRT) model, with standard normal priors on the subject abilities (ideal points), and normal priors on the item parameters. The user supplies...
/CRAN/refmans/MCMCpack/html/MCMCirtKd.html
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R: Ridge Binary Logistic Regression for Binary data
...penalization. Usage RidgeBinaryLogistic(y, X = NULL, data = NULL, freq = NULL, tolerance = 1e-05, maxiter = 100, penalization = 0.2, cte = FALSE, ref = "first", bootstrap = FALSE, nmB = 100, RidgePlot...
/CRAN/refmans/MultBiplotR/html/RidgeBinaryLogistic.html
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R: Supervised Clustering of Predictor Variables
...greedy forward strategy and optimizes a combination of the Wilcoxon and Margin statistics for finding the clusters. Usage wilma(x, y, noc, genes = NULL, flip = TRUE, once.per.clust = FALSE, trace = 0)...
/CRAN/refmans/supclust/html/wilma.html
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R: Markov Chain Monte Carlo for Robust K-Dimensional Item...
MCMCirtKdRob {MCMCpack} R Documentation Markov Chain Monte Carlo for Robust K-Dimensional Item Response Theory Model Description This function generates a posterior sample from a Robust K-dimensional...
/CRAN/refmans/MCMCpack/html/MCMCirtKdRob.html
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R: Distance-based partial least squares regression
dbplsr {dbstats} R Documentation Distance-based partial least squares regression Description dbplsr is a variety of partial least squares regression where explanatory information is coded as distances...
/CRAN/refmans/dbstats/html/dbplsr.html
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R: Fit a CATCH model and predict categorical response.
...solves classification problems and selects variables by fitting a covariate-adjusted tensor classification in high-dimensions (CATCH) model. The input training predictors include two parts: tensor...
/CRAN/refmans/catch/html/catch.html
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R: Fit a CATCH model and predict categorical response.
...solves classification problems and selects variables by fitting a covariate-adjusted tensor classification in high-dimensions (CATCH) model. The input training predictors include two parts: tensor...
/CRAN/refmans/TULIP/html/catch.html
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R: A Leaps and Bounds Algorithm for finding the best variable...
...eleaps(mat,kmin=length(include)+1,kmax=ncol(mat)-length(exclude)-1,nsol=1, exclude=NULL,include=NULL,criterion="default",pcindices="first_k",timelimit=15, H=NULL,r=0, tolval=1000*.Machine$double.eps, ...
/CRAN/refmans/subselect/html/eleaps.html
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R: Plot ROC curves and associated diagnostics
...stats = TRUE, abline.col = "grey", abline.lty = "dashed", inGroup.col = "red", outGroup.col = "blue", lty = "solid", caption = c("ROC curve", "Dissimilarity profiles", "TPF - FPF vs Dissimilarity", ...
/CRAN/refmans/analogue/html/plot.roc.html
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R: Biplot for Principal Components using ggplot2
...multidimensional dataset. The 2D biplot is typically based on the first two principal components of a dataset, giving a rank 2 approximation to the data. The “bi” in biplot refers to the fact that...
/CRAN/refmans/ggbiplot/html/ggbiplot.html
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R: Restricted Local Improvement search for an optimal k-variable...
...Restricted Local Improvement algorithm seeks a k-variable subset which is optimal, as a surrogate for the whole set, with respect to a given criterion. Usage improve( mat, kmin, kmax = kmin, nsol = 1...
/CRAN/refmans/subselect/html/improve.html
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R: Simulated Annealing Search for an optimal k-variable subset
...respect to a given criterion. Usage anneal( mat, kmin, kmax = kmin, nsol = 1, niter = 1000, exclude = NULL, include = NULL, improvement = TRUE, setseed = FALSE, cooling = 0.05, temp = 1, coolfreq = 1...
/CRAN/refmans/subselect/html/anneal.html
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R: Construction of confidence intervals for the Generalized...
...accuracy measures (sensitivity and specificity) for a continuous diagnostic test using two methods: the Generalized Pivotal Quantity (GPQ) method and the Empirical Likelihood (EL) method. Usage gsym...
/CRAN/refmans/GsymPoint/html/gsym.point.html
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R: Further functions to simulate psychological/psychometric...
...sim.simplex for a data simplex, sim.circ for a circumplex structure, sim.congeneric for a one factor factor congeneric model, sim.dichot to simulate dichotomous items, sim.hierarchical to create a...
/CRAN/refmans/psych/html/sim.omega.html
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R: Model-Based Clustering
...agglomerative clustering. The optimal model is then selected according to BIC. Usage Mclust(data, G = NULL, modelNames = NULL, prior = NULL, control = emControl(), initialization = NULL, warn = mclust...
/CRAN/refmans/mclust/html/Mclust.html
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R: Score item composite scales and find Cronbach's alpha,...
...of the direction to score them (a keys.list with k keys) find the sum scores or average scores for each person and each scale. In addition, report Cronbach's alpha, Guttman's Lambda 6, the average...
/CRAN/refmans/psych/html/score.items.html
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R: Functions to simulate psychological/psychometric data.
...basic factor analysis simulations. These functions include sim for a factor simplex, and sim.simplex for a data simplex, and sim.minor to simulate major and minor factors. Other simulations aimed at...
/CRAN/refmans/psych/html/sim.html
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R: Functions to simulate psychological/psychometric data.
...irt {psych} R Documentation Functions to simulate psychological/psychometric data. Description A number of functions in the psych package will generate simulated data with particular structures. These...
/CRAN/refmans/psych/html/sim.irt.html
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R: teigen: Function for Model-Based Clustering and...
...paradigm (by giving either training index or percentage of data taken to be known). Can be run in parallel. Usage teigen(x, Gs = 1:9, models = "all", init = "kmeans", scale = TRUE, dfstart = 50, ...
/CRAN/refmans/teigen/html/teigen.html
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R: Multidimensional IRT Copula Model
...Braeken, Tuerlinckx & de Boeck, 2007; Schroeders, Robitzsch & Schipolowski, 2014). Estimation is allowed for item difficulties, item slopes and a generalized logistic link function (Stukel, 1988).
/CRAN/refmans/sirt/html/rasch.copula.html
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