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R: Calculate stepwise PIC
stepwise.PIC {NPRED} R Documentation Calculate stepwise PIC Description Calculate stepwise PIC Usage stepwise.PIC(x, py, nvarmax = 100, alpha = 0.1) Arguments x A vector of response. py A matrix...
/CRAN/refmans/NPRED/html/stepwise.PIC.html
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R: Step III: Stepwise on the consolidated output from different...
StepIII_stepwise {GDSARM} R Documentation Step III: Stepwise on the consolidated output from different GDS runs Description Runs the stepwise regression on the output received from top models...
/CRAN/refmans/GDSARM/html/StepIII_stepwise.html
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R: Stepwise Variable Selection Procedure for Linear Regression...
My.stepwise.lm {My.stepwise} R Documentation Stepwise Variable Selection Procedure for Linear Regression Model Description This stepwise variable selection procedure (with iterations between...
/CRAN/refmans/My.stepwise/html/My.stepwise.lm.html
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R: Stepwise model selection in (graphical) interaction models
...Stepwise model selection in (graphical) interaction models Description Stepwise model selection in (graphical) interaction models Usage drop_func(criterion) ## S3 method for class 'iModel' stepwise...
/CRAN/refmans/gRim/html/stepwise.html
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R: Stepwise Variable Selection Procedure for Generalized Linear...
My.stepwise.glm {My.stepwise} R Documentation Stepwise Variable Selection Procedure for Generalized Linear Models Description This stepwise variable selection procedure (with iterations between...
/CRAN/refmans/My.stepwise/html/My.stepwise.glm.html
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R: Stepwise Variable Selection Procedure for Cox's Proportional...
My.stepwise.coxph {My.stepwise} R Documentation Stepwise Variable Selection Procedure for Cox's Proportional Hazards Model and Cox's Model Description This stepwise variable selection procedure...
/CRAN/refmans/My.stepwise/html/My.stepwise.coxph.html
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R: Compute the time to steady state using stepwise test of...
...stepwise.linear {PKNCA} R Documentation Compute the time to steady state using stepwise test of linear trend Description A linear slope is fit through the data to find when it becomes non-significant.
/CRAN/refmans/PKNCA/html/pk.tss.stepwise.linear.html
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R: Calculate stepwise high order VT in calibration
stepwise.VT {WASP} R Documentation Calculate stepwise high order VT in calibration Description Calculate stepwise high order VT in calibration Usage stepwise.VT( data, alpha = 0.1, nvarmax = 4, mode...
/CRAN/refmans/WASP/html/stepwise.VT.html
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R: Rapid Forward Stepwise Logistic Regression
...Stepwise Logistic Regression Description Roughly duplicates the following glm-style code: Usage fast_logistic_regression_stepwise_forward( Xmm, ybin, mode = "aic", pval_threshold = 0.05, use_intercept...
/CRAN/refmans/fastLogisticRegressionWrap/html/fast_logistic_regression_stepwise_forward.html
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R: Stepwise regression
stepwise {fuzzySim} R Documentation Stepwise regression Description This function runs a stepwise regression, selecting and/or excluding variables based on the significance (p-value) of the statistical...
/CRAN/refmans/fuzzySim/html/stepwise.html
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R: Main wrapper function for stepwise regression
stepwise {StepReg} R Documentation Main wrapper function for stepwise regression Description Select optimal model using various stepwise regression strategies, e.g., Forward Selection, Backward...
/CRAN/refmans/StepReg/html/stepwise.html
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R: Stepwise Discriminant Analysis
...morphodata. FToEnter significance levels for a variable to enter the subset. FToStay significance levels for a variable to stay in the subset. Details The stepdisc.calc function performs a stepwise...
/CRAN/refmans/MorphoTools2/html/stepdisc.calc.html
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R: Stepwise Variable Selection Procedure for survreg
...Stepwise Variable Selection Procedure for survreg Description This stepwise variable selection procedure can be applied to obtain the best candidates for a survreg fit. Usage srstepwise(x, times...
/CRAN/refmans/BART/html/srstepwise.html
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R: stepwise regression
stp {gtWAS} R Documentation stepwise regression Description Stepwise regression for model selection using linear model Usage stp(AllData, independent, selection = "stepwise", select = "SL", sle = 0.15...
/CRAN/refmans/gtWAS/html/stp.html
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R: conduct backward stepwise variable elimination for zero...
be.zeroinfl {mpath} R Documentation conduct backward stepwise variable elimination for zero inflated count regression Description conduct backward stepwise variable elimination for zero inflated count...
/CRAN/refmans/mpath/html/be_zeroinfl.html
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R: StepReg: Stepwise Regression Analysis
...stepwise regression analysis across various regression models such as linear, logistic, Cox proportional hazards, Poisson, and gamma regression. It incorporates diverse stepwise regression algorithms...
/CRAN/refmans/StepReg/html/StepReg-package.html
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R: Trim off non-significant variables from a model
...off non-significant variables from a model Description This function performs a stepwise removal of non-significant variables from a model, following Crawley (2005, 2007). See stepwise for a newer...
/CRAN/refmans/fuzzySim/html/modelTrim.html
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R: Forward Stepwise Selection
...Stepwise Selection Description Forward stepwise selection is a technique for feature selection in which attributes are added to a model one at a time based on their ability to improve the model's...
/CRAN/refmans/daltoolboxdp/html/fs_fss.html
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R: Stepwise item elimination
stepwiseIt {eRm} R Documentation Stepwise item elimination Description This function eliminates items stepwise according to one of the following criteria: itemfit, Wald test, Andersen's LR-test...
/CRAN/refmans/eRm/html/stepwiseIt.html
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R: Consistent Significance Controlled Variable Selection in...
...backward, stepwise) based on diverse criteria (AIC, BIC, adjusted r-square, PRESS, or p-value). The algorithm selects a final model with only significant variables defined as those with significant p-...
/CRAN/refmans/SignifReg/html/SignifReg-package.html
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R: Equipment for Logarithmic and Linear Time Stepwise Multiple Hypothesis Testing
...‘elitism’ version 1.1.1 DESCRIPTION file. Help Pages mtp Multiple Test Procedures mtp.wt Multiple Test Procedures with known true significances and non-significances p.adjust Adjust P-values...
/CRAN/refmans/elitism/html/00Index.html
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R: Stepwise forward variable selection for classification
...Stepwise forward variable selection for classification Description Performs a stepwise forward variable/model selection using the Wilk's Lambda criterion. Usage greedy.wilks(X, ...) ## Default S3...
/CRAN/refmans/klaR/html/greedy.wilks.html
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R: Customized stepwise regression with p-value and trend check...
stepFWDr {PDtoolkit} R Documentation Customized stepwise regression with p-value and trend check on raw risk factors Description stepFWDr customized stepwise regression with p-value and trend check on...
/CRAN/refmans/PDtoolkit/html/stepFWDr.html
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R: Stepwise CFA approaches
fCFA {cfa} R Documentation Stepwise CFA approaches Description These CFA methods detect and eliminate stepwise types/antitypes cells by specifying an appropriate contrast in the design matrix.
/CRAN/refmans/cfa/html/fCFA.html
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R: Bootstraps the Stepwise Algorithm of stepAIC() for Choosing a...
...Bootstraps the Stepwise Algorithm of stepAIC() for Choosing a Model by AIC Description Implements a Bootstrap procedure to investigate the variability of model selection under the stepAIC() stepwise...
/CRAN/refmans/bootStepAIC/html/boot.stepAIC.html
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R: Stepwise model selection in RCOX models
...Stepwise model selection in RCOX models Description These allow for stepwise model selection in RCOX models by. Model expansion (i.e. forward selection) is obtained by adding edge colour classes...
/CRAN/refmans/gRc/html/step.html
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R: Customized stepwise (OLS & fractional logistic) regression...
...stepwise (OLS & fractional logistic) regression with p-value and trend check Description stepFWD customized stepwise regression with p-value and trend check. Trend check is performed comparing...
/CRAN/refmans/LGDtoolkit/html/stepFWD.html
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R: Significance Controlled Variable Selection in (Generalized)...
...backward, stepwise) based on a chosen criterion (AIC, BIC, adjusted r-square, PRESS or p-value). The algorithm selects a final model with only significant variables based on a correction choice...
/CRAN/refmans/SignifReg/html/SignifReg.html
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R: Get explanatory variables of a model with significance level...
...threshold Numeric final logical if true, perform stepwise regression using step() Value A list containing the following components: sigVars names of explanatory variables which have significant levels ...
/CRAN/refmans/autoReg/html/getSigVars.html
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R: Stepwise logistic regression based on marginal information...
...Stepwise logistic regression based on marginal information value (MIV) Description stepMIV performs stepwise logistic regression based on MIV. Usage stepMIV( start.model, miv.threshold, m.ch.p.val...
/CRAN/refmans/PDtoolkit/html/stepMIV.html
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R: backward stepwise regression for RBE3 model based on the AIC...
...stepwise regression for RBE3 model based on the AIC criterion or significance. Description BE3.backward.crit implements the covariates selection based on backward and the Akaike's information criteria...
/CRAN/refmans/RBE3/html/BE3.backward.crit.html
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R: Selective inference for forward stepwise regression
...stepwise regression Description Computes p-values and confidence intervals for forward stepwise regression Usage fsInf(obj, sigma=NULL, alpha=0.1, k=NULL, type=c("active","all","aic"), gridrange=c...
/CRAN/refmans/selectiveInference/html/fsInf.html
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R: Perform stepwise regression with verifying assumptions and...
...{mlrpro} R Documentation Perform stepwise regression with verifying assumptions and identifying possible Box-Cox transformation Description A tool for multiple regression, select independent variables...
/CRAN/refmans/mlrpro/html/mlrpro-package.html
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R: FBAT-C Stepwise Strategy
...FBAT-C Stepwise Strategy Description Apply the FBAT-C test in a stepwise fashion using fbatcStrategyStep (which does forward selection with fbatcStrategyStepUp, followed by backwards selection...
/CRAN/refmans/fbati/html/fbatcStrategyStep.html
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R: Stepwise regression based on risk profile concept and raw...
...Stepwise regression based on risk profile concept and raw risk factors Description stepRPCr customized stepwise regression with p-value and trend check on raw risk factors which additionally takes...
/CRAN/refmans/PDtoolkit/html/stepRPCr.html
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R: Fetch significant markers after permutation analysis
...Fetch significant markers after permutation analysis Description Fetch significant makers after permutation analysis. These markers can be used as cofactors for model selection in a forward stepwise...
/CRAN/refmans/qtl/html/mqmfind.marker.html
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R: F.step.cjs - Stepwise model selection for CJS models.
...F.step.cjs - Stepwise model selection for CJS models. Description Conducts automated stepwise model selection of CJS models. Selection includes forward steps followed by backward looks. Steps consider...
/CRAN/refmans/mra/html/F.step.cjs.html
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R: Customized stepwise regression with p-value and trend check
stepFWD {PDtoolkit} R Documentation Customized stepwise regression with p-value and trend check Description stepFWD customized stepwise regression with p-value and trend check. Trend check is performed...
/CRAN/refmans/PDtoolkit/html/stepFWD.html
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R: Stepwise Selection Procedure for Multi-Parameter Regression...
stepmpr {mpr} R Documentation Stepwise Selection Procedure for Multi-Parameter Regression (MPR) Models Description Applies a stepwise selection procedure to an object of class “mpr” to find the...
/CRAN/refmans/mpr/html/stepmpr.html
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R: Stepwise (OLS & fractional logistic) regression based on risk...
...Stepwise (OLS & fractional logistic) regression based on risk profile concept Description stepRPC customized stepwise regression with p-value and trend check which additionally takes into account the...
/CRAN/refmans/LGDtoolkit/html/stepRPC.html
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R: Stepwise backward elimination for SGB regression
stepSGB {SGB} R Documentation Stepwise backward elimination for SGB regression Description Stepwise elimination of the non significant regression parameters. Possibility to assign a fixed value shape1...
/CRAN/refmans/SGB/html/stepSGB.html
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R: Stepwise logistic regression based on risk profile concept
stepRPC {PDtoolkit} R Documentation Stepwise logistic regression based on risk profile concept Description stepRPC customized stepwise regression with p-value and trend check which additionally takes...
/CRAN/refmans/PDtoolkit/html/stepRPC.html
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R: Graphical F Plot for Significance in Regression
GFplot {MPV} R Documentation Graphical F Plot for Significance in Regression Description This function analyzes regression data graphically. It allows visualization of the usual F-test for significance...
/CRAN/refmans/MPV/html/GFplot.html
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R: Multivariate Modeling with Stepwise Cluster Analysis
rSCA.modeling {rSCA} R Documentation Multivariate Modeling with Stepwise Cluster Analysis Description This function models the relationship between multivariate dependent variable and independent ones.
/CRAN/refmans/rSCA/html/rSCA.modeling.html
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R: Fits a population tree to data from quartet concordance...
...uses a stepwise search to find the best resolution of that guide tree. Any unresolved edge corresponds to ancestral panmixia, on which the coalescent process is assumed. Usage stepwise.test.tree(cf...
/CRAN/refmans/phylolm/html/stepwise.test.tree.html
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R: MEDUSA: modeling evolutionary diversification using stepwise...
...via a stepwise AIC approach. Usage medusa(phy, richness = NULL, criterion = c("aicc", "aic"), partitions=NA, threshold=NA, model = c("mixed", "bd", "yule"), cut = c("both","stem","node"), stepBack...
/CRAN/refmans/geiger/html/medusa.html
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R: Backwards Stepwise Selection of Positive-Negative Richards...
pn.modselect.step {FlexParamCurve} R Documentation Backwards Stepwise Selection of Positive-Negative Richards nlslist Models Description This function performs backawards stepwise model selection...
/CRAN/refmans/FlexParamCurve/html/pn.modselect.step.html
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R: Stepwise fitting of angular mixture models with incremental...
fit_incremental_angmix {BAMBI} R Documentation Stepwise fitting of angular mixture models with incremental component sizes and optimum model selection Description Stepwise fitting of angular mixture...
/CRAN/refmans/BAMBI/html/fit_incremental_angmix.html
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R: Genome and Transcriptome Wide Association
...Usage Association(Tdata,alldata,independent="B(E)",Elevels=c(0.05,0.95),selection="stepwise", select="SL",Choose=NULL,SL=c(0.05,0.15,0.15),correct="Bonferroni") Arguments Tdata Phenotye data alldata...
/CRAN/refmans/gtWAS/html/Association.html
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R: Multiple Testing Method to Control Generalized Family-Wise...
...stepwise procedures to conduct multiple hypotheses testing. The details of the stepwise algorithm can be found in Romano and Wolf (2007) <DOI:10.1214/009053606000001622> and Hsu, Kuan, and Yen (2014)...
/CRAN/refmans/StepwiseTest/html/StepwiseTest-package.html
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R: coxSW
...conducts a stepwise Cox regression analysis on survival data, leveraging the capabilities of the My.stepwise R package. The primary objective of this function is to identify the most significant...
/CRAN/refmans/Coxmos/html/coxSW.html
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R: GLMs with variable selection for multiple species
...output form. Usage multGLM(data, sp.cols, var.cols, id.col = NULL, block.cols = NULL, family = "binomial", test.sample = 0, FDR = FALSE, correction = "fdr", FDR.first = TRUE, corSelect = FALSE, coeff = ...
/CRAN/refmans/fuzzySim/html/multGLM.html
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R: StepReg Shiny App
...StepReg Shiny App Description StepRegShinyApp is a Shiny application designed for performing stepwise regression analysis. In Step 1, users can upload their dataset, configure settings such as header...
/CRAN/refmans/StepReg/html/StepRegShinyApp.html
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R: The Gaussian Covariate Method for Variable Selection
...boston Boston data decode Decodes the number of a subset selected by fasb.R to give the covariates f1st Stepwise selection of covariates f2st Repeated stepwise selection of covariates f3st Stepwise...
/CRAN/refmans/gausscov/html/00Index.html
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R: Unsupervised Spatial Filtering with Eigenvectors in Linear...
Eigenvectors are selected by an unsupervised stepwise regression technique. Supported selection criteria are the minimization of residual autocorrelation, maximization of model fit, significance of...
/CRAN/refmans/spfilteR/html/lmFilter.html
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R: Linear Modelling Utility Functions
...Utility functions to build linear models using Phylogenetic Eigenvector Maps among their explanatory variables. Usage lmforwardsequentialAICc(y, x, object) lmforwardsequentialsidak(y, x, object, alpha...
/CRAN/refmans/MPSEM/html/lm-utils.html
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R: Q-matrix validation
...(sequential) G-DINA model based on PVAF (de la Torre & Chiu, 2016; Najera, Sorrel, & Abad, 2019; Najera et al., 2020), stepwise Wald test (Ma & de la Torre, 2020) or mesa plot (de la Torre & Ma, 2016).
/CRAN/refmans/GDINA/html/Qval.html
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R: Fit best ARIMA model to univariate time series
...max.q = 5, max.P = 2, max.Q = 2, max.order = 5, max.d = 2, max.D = 1, start.p = 2, start.q = 2, start.P = 1, start.Q = 1, stationary = FALSE, seasonal = TRUE, ic = c("aicc", "aic", "bic"), stepwise...
/CRAN/refmans/forecast/html/auto.arima.html
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R: Gauss-Dantzig Selector - Aggregation over Random Models...
...Aggregation over Random Models (GDS-ARM) Description The GDS-ARM procedure consists of three steps. First, it runs the Gauss Dantzig Selector (GDS) nrep times, each time with a different set of nint...
/CRAN/refmans/GDSARM/html/GDSARM.html
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R: Design and Analysis of Experiments with R
...Two-period crossover study of antifungal agent Apo apolipoprotein survey varaince component study apple Confounded apple slice browning experiment arso 2^{(7-3)} arsenic removal experiment augm ...
/CRAN/refmans/daewr/html/00Index.html
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R: Fuzzy Similarity in Species Distributions
...Fuzzy Similarity in Species Distributions appendData Append data bioThreat Biotic threat of a stronger over a weaker species based on their favourability values cleanCoords Clean coordinates corSelect...
/CRAN/refmans/fuzzySim/html/00Index.html
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R: An Effective Design Based Model Fitting Method for Definitive...
...to a Definitive Screeing Design by first restricting main effects to the smallest main effects and those significant at at least the .20 level in a main effects model. Next forward stepwise selection...
/CRAN/refmans/daewr/html/FitDefSc.html
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R: Automatic Linear and Logistic Regression and Survival Analysis
...gaze addLabelData Add labels to data adjustedPlot Draw an expected plot adjustedPlot.survreg Draw predicted survival curve with an object survreg adjustedPlot2 Draw a survfitted plot adjustedPlot2...
/CRAN/refmans/autoReg/html/00Index.html
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R: Variable selection for alternatives to the Poisson and...
...hybrid versions of forward stepwise and backward stepwise by comparing hierarchically builded candidate models using a criterion previously specified such as AIC, BIC or p-value of the significance...
/CRAN/refmans/glmtoolbox/html/stepCriterion.overglm.html
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R: Function to perform multiple RMST-based tests
...hypotheses of the restricted mean survival times (RMSTs) of k different groups can be tested simultaneously. Therefore, the multivariate distribution of local Wald-type test statistics is approximated...
/CRAN/refmans/GFDrmst/html/RMST.test.html
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R: 'CASMI'-Based Feature Selection
...issue. (synonyms of "feature": "variable" "factor" "attribute") For more information, please refer to the corresponding publication: Shi, J., Zhang, J. and Ge, Y. (2019), "CASMI—An Entropic Feature...
/CRAN/refmans/CASMI/html/CASMI.selectFeatures.html
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R: Phylogenetic eigenvectors regression.
...the traits under analysis) estimated values express phylogenetic trends in data and residuals express independent evolution of each species. Usage PVR(x,phy,trait,envVar,method="moran",weights, ...
/CRAN/refmans/PVR/html/PVR.html
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R: Perform AIC forward selection for nrm.
...for nrm. Usage nrmSelection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... ) nrm_selection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL...
/CRAN/refmans/ghypernet/html/nrm_selection.html
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R: Trend Surface Analysis for multiple species
It converts categorical presence-absence (1-0) data into continuous surfaces denoting the spatial trend in species' occurrence patterns. Usage multTSA(data, sp.cols, coord.cols, id.col = NULL, degree...
/CRAN/refmans/fuzzySim/html/multTSA.html
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R: Latent Environmental & Genetic InTeraction (LEGIT) Model
...bootstrap_var_select Bootstrap variable selection (for IMLEGIT) elastic_net_var_select Elastic net for variable selection in IMLEGIT model example_2way Simulated example of a 2 way interaction GxE ...
/CRAN/refmans/LEGIT/html/00Index.html
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R: Unsupervised Spatial Filtering with Eigenvectors in...
Eigenvectors are selected by an unsupervised stepwise regression technique. Supported selection criteria are the minimization of residual autocorrelation, maximization of model fit, significance ...
/CRAN/refmans/spfilteR/html/glmFilter.html
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R: Partial pruning of multi-group models
...is called partial pruning (Epskamp, Isvoranu, & Cheung, 2020; Haslbeck, 2020). The algorithm is as follows: 1. remove all parameters not significant at alpha in all groups (without equality constrains)...
/CRAN/refmans/psychonetrics/html/partialprune.html
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R: Estimation and Additional Tools for Quantile Generalized Beta Regression Model
...NEWS. Help Pages BE3.backward.crit backward stepwise regression for RBE3 model based on the AIC criterion or significance. dBE3 The Generalized Beta Distribution dgumbel2 The Gumbel2 distribution ML...
/CRAN/refmans/RBE3/html/00Index.html
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R: Construct and filter n-grams
...Construct and filter n-grams Description Builds and selects important n-grams stepwise. Usage construct_ngrams( target, seq, u, n_max, conf_level = 0.95, gap = TRUE, use_heuristics = TRUE...
/CRAN/refmans/biogram/html/construct_ngrams.html
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R: Finemap multiple signals in a single dataset
...where they exist, via conditioning or masking - ie a stepwise procedure Usage finemap.signals( D, LD = D$LD, method = c("single", "mask", "cond"), r2thr = 0.01, sigsnps = NULL, pthr = 1e-06, maxhits...
/CRAN/refmans/coloc/html/finemap.signals.html
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R: Combinatorial search (all possible subset) for regression...
...combinatorial (exhaustive) search algorithm, aka all-possible-subsets regression. As opposed to the sequential approach (stepwise, forward addition, or backward elimination) that has a potential bias...
/CRAN/refmans/DJL/html/ma.aps.reg.html
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R: REGWQ - Ryan / Einot and Gabriel / Welsch test procedure...
...REGWQ - Ryan / Einot and Gabriel / Welsch test procedure This function computes REGWQ test for given data including p samples. It is based on a stepwise or layer approach to significance testing.
/CRAN/refmans/mutoss/html/regwq.html
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R: Bonferroni Method
...combined. adjust character string to specify an adjustment method to account for dependence. The default is "none", in which case no adjustment is applied. Methods "nyholt", "liji", "gao", or "galwey"...
/CRAN/refmans/poolr/html/bonferroni.html
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R: 'FWDselect': Selecting Variables in Regression Models.
...to select the best model using different types of data (binary, Gaussian or Poisson) and applying it in different contexts (parametric or non-parametric). The proposed method is a new forward stepwise-...
/CRAN/refmans/FWDselect/html/FWDselect.html
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R: Summaries of models when removing a predictor in a...
...drop1summary(fit, scope, alpha = 0.05, adjust.method = "fdr", sort.by = "p-value") Arguments fit an lm or glm object representing a model. scope defines the range of models examined in the stepwise...
/CRAN/refmans/SignifReg/html/drop1summary.html
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R: Binomial Test
binomtest {poolr} R Documentation Binomial Test Description Function to carry out the binomial test. Usage binomtest(p, adjust = "none", R, m, size = 10000, threshold, side = 2, batchsize, nearpd...
/CRAN/refmans/poolr/html/binomtest.html
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R: Summaries of models when adding a predictor in (generalized)...
...add1summary(fit, scope, alpha = 0.05, adjust.method = "fdr", sort.by = "p-value") Arguments fit an lm or glm object representing a model. scope defines the range of models examined in the stepwise...
/CRAN/refmans/SignifReg/html/add1summary.html
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R: Student - Newman - Keuls rejective test procedure.
...Student - Newman - Keuls rejective test procedure. The procedure controls the FWER in the WEAK sense. Usage snk(formula, data, alpha, MSE=NULL, df=NULL, silent=FALSE) snk.wrapper(model, data, alpha...
/CRAN/refmans/mutoss/html/snk.html
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R: Nonparametric multiple test procedure for all-pairs...
...all-pairs comparisons by Gao et al. (2008). This procedure is a nonparametric equivalent of Campbell and Skillings (1981) sequential test procedure. Usage gao_cs(formula, data, alpha = 0.05, silent...
/CRAN/refmans/nparcomp/html/gao_cs.html
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R: Separate analysis for binary data adjusted for periods
...into account concurrent controls) using a logistic model and adjusting for periods, if the treatment arm stays in the trial for more than one period. Usage sepmodel_adj_bin(data, arm, alpha = 0.025...
/CRAN/refmans/NCC/html/sepmodel_adj_bin.html
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R: Tippett's Method
tippett {poolr} R Documentation Tippett's Method Description Function to carry out Tippett's method. Usage tippett(p, adjust = "none", R, m, size = 10000, threshold, side = 2, batchsize, nearpd = TRUE...
/CRAN/refmans/poolr/html/tippett.html
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R: Step-wise exploratory search for optimal fitting model
...stepwise search to optimize the structure of omega_theta, omega_psi, theta or psi. Starts at empty or full structure and iteratively adds or removes edges to optimize the criterion. Usage lvnetSearch...
/CRAN/refmans/lvnet/html/lvnetSearch.html
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R: print a cross-validated glmnet object
...x fitted 'cv.glmnet' object digits significant digits in printout ... additional print arguments Details A summary of the cross-validated fit is produced, slightly different for a 'cv.relaxed' object...
/CRAN/refmans/glmnet/html/print.cv.glmnet.html
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R: Frequentist logistic regression model analysis for binary...
...taking into account all trial data until the arm under study leaves the trial and adjusting for calendar time units as factors. Usage fixmodel_cal_bin( data, arm, alpha = 0.025, unit_size = 25, ncc...
/CRAN/refmans/NCC/html/fixmodel_cal_bin.html
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R: Drop a predictor to a (generalized) linear regression model...
...Significance Controlled Variable Selection method Description drop1SignifReg removes from the model the predictor, out of the current predictors, which minimizes the criterion (AIC, BIC, r-ajd, PRESS...
/CRAN/refmans/SignifReg/html/drop1SignifReg.html
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R: Fisher's Method
fisher {poolr} R Documentation Fisher's Method Description Function to carry out Fisher's method. Usage fisher(p, adjust = "none", R, m, size = 10000, threshold, side = 2, batchsize, nearpd = TRUE...
/CRAN/refmans/poolr/html/fisher.html
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R: Frequentist logistic regression model analysis for binary...
...performs logistic regression taking into account all trial data until the arm under study leaves the trial and adjusting for periods as factors. Usage fixmodel_bin(data, arm, alpha = 0.025, ncc = TRUE...
/CRAN/refmans/NCC/html/fixmodel_bin.html
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R: Stouffer's Method
stouffer {poolr} R Documentation Stouffer's Method Description Function to carry out Stouffer's method. Usage stouffer(p, adjust = "none", R, m, size = 10000, threshold, side = 2, batchsize, nearpd...
/CRAN/refmans/poolr/html/stouffer.html
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R: Graphical Regression Plot
...This function analyzes regression data graphically. It allows visualization of the usual F-test for significance of regression. Usage GRegplot(X, y, sortTrt=FALSE, includeIntercept=TRUE, type="hist")...
/CRAN/refmans/MPV/html/GRegplot.html
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R: Add a predictor to a (generalized) linear regression model...
...Significance Controlled Variable Selection method Description add1SignifReg adds to the model the predictor, out of the available predictors, which minimizes the criterion (AIC, BIC, r-ajd, PRESS, max...
/CRAN/refmans/SignifReg/html/add1SignifReg.html
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R: Epidemiological capture-recapture Data on HIV
...-recapture data on HIV from four reporting centers in Rome, Italy. Usage HIV Format 15 by 5 numeric matrix, with the following columns: c1, c2, c3, c4 Capture histories from the four capture occasions...
/CRAN/refmans/Rcapture/html/HIV.html
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R: Ensemble blocks regression
...regression without any check of the estimated coefficients (e.g. statistical significance or sign of the estimated coefficients). Usage ensemble.blocks(method, target, db, blocks, reg.type = "ols", p...
/CRAN/refmans/LGDtoolkit/html/ensemble.blocks.html
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R: KCP on the running statistics
...Change Point) detection. A KCP permutation test is first implemented to confirm whether there is at least one change point (k>0) in the running statistics. If this permutation test is significant, a...
/CRAN/refmans/kcpRS/html/kcpRS-package.html
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R: Percentage Difference of Means and Variances
...the entire collection (EC) and core set (CS). Percentage of significant differences of mean (\(MD\%_{Hu}\)) (Hu et al. 2000) Percentage of significant differences of variance (\(VD\%_{Hu}\)) (Hu et al.
/CRAN/refmans/EvaluateCore/html/percentdiff.evaluate.core.html
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R: Subsampling Winner Algorithm for Variable Selection in the...
...on the subsampled variables. Variables are scored based on the AUC and the t-statistics in linear regression. Variables then enter a competition and the semi-finalists will be used in a final round of ...
/CRAN/refmans/swa/html/swa.html
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