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| RVAideMemoire-package | Diverse basic statistical and graphical functions |
| bootstrap | Bootstrap |
| byf.hist | Histogram for factor levels |
| byf.mqqnorm | QQ-plot for factor levels |
| byf.mshapiro | Shapiro-Wilk test for factor levels |
| byf.normhist | Histogram and normal distribution for factor levels |
| byf.qqnorm | QQ-plot for factor levels |
| byf.shapiro | Shapiro-Wilk test for factor levels |
| chisq.bintest | Pearson's Chi-squared test or Fisher's exact test for binary variables |
| chisq.exp | Expected counts for comparison of proportions to given values |
| chisq.multcomp | Pairwise comparisons after a chi-squared goodness-of-fit test |
| chisq.theo.multcomp | Pairwise comparisons after a chi-squared test for given probabilities |
| cochran.qtest | Cochran's Q test |
| cor.2comp | Comparison of 2 Pearson's linear correlation coefficients |
| cor.conf | Equality of a Pearson's linear correlation coefficient to a given value |
| cor.multcomp | Comparison of several Pearson's linear correlation coefficients |
| cox.resid | Martingale residuals of a Cox model |
| cramer.test | Cramer's association coefficient |
| cv | Coefficient of variation |
| DA.confusion | Classification error rate of a Discriminant Analysis |
| DA.valid | Cross-validation in Discriminant Analysis |
| DA.var | Explained variance in Discriminant Analysis |
| dendro.gp | Dendrogram and number of groups to be chosen |
| fc.multcomp | Pairwise comparisons for the interaction between a factor and a covariate |
| fisher.multcomp | Pairwise comparisons after a test for independence of 2 categorical variables |
| G.multcomp | Pairwise comparisons after a G-test |
| G.test | G-test |
| G.theo.multcomp | Pairwise comparisons after a G-test for given probabilities |
| ind.contrib | Individual contributions in regression |
| LDA.format | Re-formating LDA data |
| least.rect | Least rectangles linear regression |
| logis.fit | Graphical adujstment of a simple binary logistic regression to data |
| logis.noise | Creating a nls model for logistic regression from fitted values of a glm model |
| mod | Mode |
| mqqnorm | Multivariate normality QQ-Plot |
| mshapiro.test | Shapiro-Wilk multivariate normality test |
| overdisp.glmer | Estimation of overdispersion with 'glmer' models |
| pairwise.G.test | Pairwise comparisons for proportions using G-tests |
| pairwise.manova | Pairwise MANOVAs |
| pairwise.perm.t.test | Pairwise permutational t tests |
| perm.anova | Permutational Analysis of Variance |
| perm.bartlett.test | Permutational Bartlett's test of homogeneity of variances |
| perm.cor.test | Permutational Pearson's correlation test |
| perm.t.test | Permutational Student's t-test |
| perm.var.test | Permutational F test to compare two variances |
| plot1comp.ind | Plot of indiviuals and their class on a single axis (component) |
| plot1comp.var | Plot of correlation between predictor variables and a single component |
| plotresid | Simple analysis of model residuals |
| plotsurvivors | Survivor curve |
| PLSDA.ncomp | Graphical help to number of components selection in PLS-DA |
| PLSDA.test | Permutational test for the discriminant ability of the factor in PLS-DA |
| PLSDA.VIP | Variable Importance in the Projection (VIP) |
| predict.least.rect | Predict method for least rectangles linear regression |
| print.byf.test | Print method |
| print.chisq.exp | Expected counts for comparison of proportions to given values |
| print.DA.confusion | Classification error rate of a Discriminant Analysis |
| print.DA.valid | Cross-validation in Discriminant Analysis |
| print.least.rect | Least rectangles linear regression |
| print.PLSDA.VIP | Variable Importance in the Projection (VIP) |
| print.RV.multcomp | Print method |
| print.RVtest | Print method |
| prop.multcomp | Pairwise comparisons after a test for given proportions |
| reg.ci | Confidence intervals of a simple linear regression |
| RVAideMemoire | Diverse basic statistical and graphical functions |
| scat.mix.categorical | Representation of qualitative variables in Hill and Smith mix analysis |
| scat.mix.numeric | Representation of numeric variables in Hill and Smith mix analysis |
| se | Standard error of the mean |
| seq2 | Sequence generation |
| spearman.ci | Confidence interval of a Spearman's rank correlation coefficient |
| summary.least.rect | Summary method for least rectangles linear regression |
| user.cont | User defined contrasts for LSMeans |
| wilcox.paired.multcomp | Non parametric pairwise comparisons for paired data |
| wilcox.signtest | Wilcoxon sign test |