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| dad-package | Three-Way Data Analysis Through Densities |
| append.df2folderh | Adds a data frame to a 'folderh'. |
| appendtofolderh | Adds a data frame to a 'folderh'. |
| as.data.frame.folder | Folder to data frame |
| as.data.frame.folderh | Hierarchic folder to data frame |
| as.folder | Coerce to a folder |
| as.folder.data.frame | Data frame to folder |
| as.folder.folderh | Hierarchic folder to folder |
| bandwidth.parameter | Parameter of the normal reference rule |
| castles.dated | Dated castles |
| castles.nondated | Alsacian castles |
| cor.folder | Correlation matrices of a folder of data sets |
| corf | Correlation matrices of a folder of data sets |
| dad | Three-Way Data Analysis Through Densities |
| df2folder | Data frame to folder |
| dist.l2d.gp | Distance between probability densities |
| dist.l2d.gp.u | Distance between probability densities |
| dist.l2d.gs | Distance between probability densities |
| dist.l2d.gs.u | Distance between probability densities |
| dist.l2d.kga | Distance between probability densities |
| dist.l2d.kga.u | Distance between probability densities |
| dist.l2d.kgw | Distance between probability densities |
| dist.l2d.kgw.u | Distance between probability densities |
| distl2d | Distance between probability densities |
| distl2dpar | Distance between probability densities |
| fdiscd.misclass | Misclassification ratio in functional discriminant analysis of probability densities. |
| fdiscd.predict | Predicting the class of a group of individuals with discriminant analysis of probability densities. |
| fmdsd | Multidimensional scaling of probability densities |
| folder | Folder of data sets |
| folder2df | Folder to data frame |
| folderh | Hierarchic folder of n data frames related in pairs by (n-1) keys |
| folderh2df | Hierarchic folder to data frame |
| folderh2folder | Hierarchic folder to folder |
| fpcad | Functional PCA of probability densities |
| interpret | Scores of the 'fpcad' or 'fmdsd' function vs. moments of the densities |
| interpret.fmdsd | Scores of the 'fmdsd' function vs. moments of the densities |
| interpret.fpcad | Scores of the 'fpcad' function vs. moments of the densities |
| is.fdiscd.misclass | Class 'fdiscd.misclass' |
| is.fdiscd.predict | Class 'fdiscd.predict' |
| is.fmdsd | Class 'fmdsd' |
| is.folder | Class 'folder' |
| is.folderh | Class 'folderh' |
| is.fpcad | Class 'fpcad' |
| kurtosis.folder | Kurtosis coefficients of a folder of data sets |
| kurtosisf | Kurtosis coefficients of a folder of data sets |
| l2d | L^2 inner product of estimated probability densities |
| l2d.gp | L^2 inner product of Gaussian densities |
| l2d.gp.u | L^2 inner product of Gaussian densities |
| l2d.gs | L^2 inner product of estimated probability densities |
| l2d.gs.u | L^2 inner product of estimated probability densities |
| l2d.kga | L^2 inner product of estimated probability densities |
| l2d.kga.u | L^2 inner product of estimated probability densities |
| l2d.kgw | L^2 inner product of estimated probability densities |
| l2d.kgw.u | L^2 inner product of estimated probability densities |
| l2dpar | L^2 inner product of Gaussian densities |
| mat.dist.l2d.gp | Matrix of L^2 distances |
| mat.dist.l2d.gp.u | Matrix of L^2 distances |
| mat.dist.l2d.gs | Matrix of L^2 distances |
| mat.dist.l2d.gs.u | Matrix of L^2 distances |
| mat.dist.l2d.kga | Matrix of L^2 distances |
| mat.dist.l2d.kga.u | Matrix of L^2 distances |
| mat.dist.l2d.kgw | Matrix of L^2 distances |
| mat.dist.l2d.kgw.u | Matrix of L^2 distances |
| mat.ip.l2d.gp | Matrix of L^2 inner products |
| mat.ip.l2d.gp.u | Matrix of L^2 inner products |
| mat.ip.l2d.gs | Matrix of L^2 inner products |
| mat.ip.l2d.gs.u | Matrix of L^2 inner products |
| mat.ip.l2d.kga | Matrix of L^2 inner products |
| mat.ip.l2d.kga.u | Matrix of L^2 inner products |
| mat.ip.l2d.kgw | Matrix of L^2 inner products |
| mat.ip.l2d.kgw.u | Matrix of L^2 inner products |
| matdistl2d | Matrix of L^2 distances |
| matdistl2dpar | Matrix of L^2 distances |
| matipl2d | Matrix of L^2 inner products |
| matipl2dpar | Matrix of L^2 inner products |
| mean.folder | Means of a folder of data sets |
| meanf | Means of a folder of data sets |
| plot.fmdsd | Plotting scores of multidimensional scaling of density functions |
| plot.fpcad | Plotting scores of principal component analysis of density functions |
| plotframes | Plotting of two sets of variables |
| print.fdiscd.misclass | Printing results of discriminant analysis of probability density functions |
| print.fdiscd.predict | Printing results of discriminant analysis of probability density functions |
| print.fmdsd | Printing results of a multidimensional scaling analysis of probability densities |
| print.fpcad | Printing results of a functional PCA of probability densities |
| roseflowers | Rose flowers |
| roseleaves | Rose leaves |
| roses | Roses data |
| skewness.folder | Skewness coefficients of a folder of data sets |
| skewnessf | Skewness coefficients of a folder of data sets |
| sqrtmatrix | Square root of a symmetric, positive semi-definite matrix |
| summary.folder | Summarize a folder |
| summary.folderh | Summarize a folderh |
| var.folder | Variance matrices of a folder of data sets |
| varf | Variance matrices of a folder of data sets |