transformations from 'mixtures' to  'compositions' classes

Composition of glaciar sediments from the Aar massif (Switzerland)
Activity patterns of a statistician for 20 days
Artic lake sediment samples of different water depth
Compositions and depth of 25 specimens of boxite
Color-size compositions of 20 clam colonies from East Bay
Color-size compositions of 20 clam colonies from West Bay
Compositional Linear Model of Coregionalisation
Compositions, depths and porosities of 25 specimens of coxite
Compositions and total pebble counts of 92 glacial tills
Hydrochemical composition data set of Llobregat river basin water (NE Spain)
Steroid metabolite patterns in adults and children
Proportions of sand, silt and clay in sediments specimens
Serum Protein compositions of blood samples
AFM compositions of 23 aphyric Skye lavas
Proportions of supervisor's statements assigned to different categories
White-cell composition of 30 blood samples by two different methods
Marginal compositions in Aitchison Compositions
vectorial arithmetic for data sets with aplus class
Convert "compositions" classes to data frames or matrices
Drawing a 3D coordiante system to a plot, based on package rgl
Automatic common backtransformation for compositions
Compute balances for a compositional dataset.
Three-dimensional biplots, based on package rgl
Displaying compositions and amounts with box-plots
Convert between clr and ilr, and between cpt and ipt.
Heuristics to find subpopulations of outliers
Dendrogram representation of acomp or rcomp objects
A biplot providing somewhat easier access to details of the plot.
Create a color/char palette or for groups of outliers
The policy of treatment of missing values in the "compositions" package
Correlations of amounts and compositions
Recast amounts as mixtures of end-members
Gets the detection limit stored in the data set
The canonical basis in the clr plane used for ilr and ipt transforms.
Internal functions: Parallel operations of single and multiple datasets
Internal function: give a derived subclass to an object
Internal functions of the compositions package
Internal function: row and column sums of matrices
Internal functions: Get the diagonal of a matrix
Internal functions: Generate a diagonal matrix
Internal function: Checking equality of IEEE special numbers
Calling from a function with the own parameters
Interal function: Get number of samples and number of parts in a compositional object
An auxiliary functions to compute user-defined ilr and ipt transforms.
Environment containing the old gsi functions
Internal function: Can something be considered as a single multivariate data item?
Internal functions: Storing integers as reals
Internal function: Compute a desired compositional margin
Auxiliary functions to compute user-defined ilr and ipt transforms.
Internal function: Convert to plain vector or matrix
Internal function: Recode missings with IEEE number and vice versa
Internal function: Reshape an object to the shape type of another
Internal function: Solves singular and non square equation systems
Internal function: A panel displaying a label only
Internal function: computes variance of compositional data set with missing/zero values
Density estimation on the simplex with Dirichlet kernel
Ploting composition into rotable tetrahedron
Draws connected lines from point to point.
Compute Mahalanobis distances based von robust Estimations
inner product for datasets with a vector space structure
Returns a projector the the observed space in case of missings.
Classify and summarize missing values in a dataset
Transformations from 'mixtures' to 'compositions' classes
Metric summary statistics of real, amount or compositional data
Treating single compositions as one-row datasets
Detect and classify compositional outliers.
Plot various graphics to analyse outliers.
Creates a paneled plot like pairs for two different datasets.
Principal component analysis for Aitchison compositions
Principal component analysis for amounts in log geometry
Principal component analysis for real compositions
Principal component analysis for real data
Principal component analysis for real amounts
Plots of pairwise logratio against a covariable.
Normal quantile plots for compositions and amounts
Compositions as elements of the simplex embedded in the D-dimensional real space
Arithmetic operations for compositions in a real geometry
Modify parameters of compositional plots.
Compute distributions of empirical Mahalanobis distances based on simulations
vectorial arithmetic for datasets in a classical vector scale
inner product for datasets with vector scale
Handling robustness issues and outliers in compositions.
Amounts i.e. positive numbers analysed as objects of the real vector space
vectorial arithmetic for data sets with rplus class
Simulate count compositions without overdispersion
Normalizing datasets by centering and scaling
Draws straight lines from point to point.
Artifical simulation of various kinds of missings/polluted data
Splitting datasets in groups given by factors
Summarizing a compositional dataset in terms of ratios
Summary of compositions in real geometry
Compute the global projector to the observed subspace.
Variances and covariances of amounts and compositions
Variation matrices of amounts and compositions
Variance covariance matrix of parameters in compositional regression
Standard R functions wrapped for compatibility