Keywords - Function Groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

xclust

adap
performs an adaptive K-means cluster analysis
adaptive
performs an adaptive K-means cluster analysis with appropriate (adaptive) multivariate graphic using the principal components
aerlb
computes the Lachenbruch-Mickey unbiased estimate of the actual discrimination error rate
cartdisptree
plots the regression/classification tree of CART in a display.
cartdrawpdfclass
generates TEX classification tree (to the file)
cartdrawpdfregr
generates TEX file of regression tree
cartleafnum
returns number of terminal (leaf) nodes in the tree.
cartpredict
classifies the data in accordance with constructed Tree.
cartsplitclass
builds the classification tree.
cartsplitregr
builds the regression tree.
carttrimp
returns the measure of tree impurity for both classification/regression tree
conting
crosses two categorical variables (for instance partitions from cluster analysis) and builds up contingency table
contmax
computes a linkage table between the rows and columns of a contingency table by maximum value of correspondence. The number of correspondences is the minimum of number or dimensions of the contingency table.
cor2dist
transforms the values of the upper triangle of a correlation matrix into distances, and it stores these distances into a vector regarding the sequence described in agglom
dentoreg
transforms density data to regression data using variance stabilizing transform. Divides the sample space into bins, calculates the counts y_i of observations from every bin, and gives the values 2*sqrt(y_i+3/8) as a regression variable.
denvalues
given a binary tree produced by cartsplit, normalizes the mean values of the leaves so that the function represented by the binary tree integrates to one.
discrim
computes the discrimination function for an observation x given the samples x1 and x2
divisive
performs an adaptive divisive K-means cluster analysis with appropriate (adaptive) multivariate graphic using principal components
grcarttree
generates the graphical objects for the regression/classification trees.
kmcont
performes a K-means cluster analysis of the rows of a contingency table including the multivariate graphic using the correspondence analysis; makes available the factorial coordinates (scores)
lpdist
computes the so-called Lp-distances between the rows of a data matrix. In the case p=1 (absolute metric) or p=2 (Euclidean metric) one should favour the function DISTANCE.
mat2vec
stores the upper triangle of a symmetric matrix into a vector regarding the sequence described in agglom
measure
computes coefficients of association between two partitions which are crossed and build up a contingency table
printingList
auxiliary quantlet for grcarttree Generates vectors of characters to be displayed. For the non-terminal nodes prints the splitting variable and the splitting point. The information is printed in the following form: "X1<=5.2", that is, variables are denoted with X1,...,Xp. For the terminal nodes the
pswap
exchanges the category labels of a vector into other ones. Here the old category labels as well as the targed category labels have to be specified. Don't specify categories which should remain unchanged
recode
allocates categories 1,2,...,L to intervals of categories. The upper bounds of the intervals have to be specified. It is an useful tool to join classes and hence to collaps contingency tables.
svm
returns the vector of scores for the objects represented in AC. AT is a training set where the last column describes the class of an object (must be +1 or -1).
svmplot
support quantlet providing graphical output for svm.xpl.
svmplotcol
support quantlet providing graphical output for svm.xpl.
vec2mat
stores the values of a vector into the upper triangle of a symmetric matrix regarding the sequence described in agglom
volumes
auxiliary quantlet for cartsplit, creates a vector of volumes: for each node of the tree "tr", calculates the volume of the rectangle corresponding to the node.
wardcont
performes Ward's hierarchical cluster analysis of the data of the rows and the columns of a contingency table including the multivariate graphic using the correspondence analysis; makes the factorial coordinates of the points in a row and in a column available
xcfcgk
performs a fuzzy Gustafson-Kessel cluster analysis.
xcfcme
Performs a fuzzy c-means cluster analysis
xchcme
Performs a hard c-means cluster analysis
xclustmain
loads the xplore library
xclusttest
tests all quantlets of xclust

Keywords - Function Groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

(C) MD*TECH Method and Data Technologies, 05.02.2006Impressum