# robCompositions v2.1.0

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## Compositional Data Analysis

Methods for analysis of compositional data including robust
methods, imputation, methods to replace rounded zeros, (robust) outlier
detection for compositional data, (robust) principal component analysis for
compositional data, (robust) factor analysis for compositional data, (robust)
discriminant analysis for compositional data (Fisher rule), robust regression
with compositional predictors and (robust) Anderson-Darling normality tests for
compositional data as well as popular log-ratio transformations (addLR, cenLR,
isomLR, and their inverse transformations). In addition, visualisation and
diagnostic tools are implemented as well as high and low-level plot functions
for the ternary diagram.

## Readme

# {robCompositions}

Robust Methods for Compositional Data

```
using robCompositions
```

data(expenditures)

p1 <- pcaCoDa(expenditures)

plot(p1)

## What is it?

- Imputation of compositional data including robust methods, methods to impute rounded zeros
- Outlier detection for compositional data using robust methods
- Principal component analysis for compositional data using robust methods
- Factor analysis for compositional data using robust methods
- Discriminant analysis for compositional data (Fisher rule) using robust methods
- Robust regression with compositional predictors
- Anderson-Darling normality tests for compositional data
- log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations).
- In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the
`ternary diagram.`

## Goals

- never use classical statistical methods on raw compositional data again.

## Getting Started

### Dependencies

The package has dependencies on

```
R (>= 2.10), utils, robustbase, rrcov, car (>= 2.0-0), MASS, pls
```

### Installation

Installion of `robCompositions`

is really easy for registered users (when the R-tools are installed). Just use

```
library(devtools)
install_github("robCompositions", "matthias-da")
```

## Examples

#### k nearest neighbor imputation

data(expenditures)

expenditures[1,3]

expenditures[1,3] <- NA

impKNNa(expenditures)$xImp[1,3]

#### iterative model based imputation

data(expenditures)

x <- expenditures

x[1,3]

x[1,3] <- NA

xi <- impCoda(x)$xImp

xi[1,3]

s1 <- sum(x[1,-3])

impS <- sum(xi[1,-3])

xi[,3] * s1/impS

xi <- impKNNa(expenditures)

xi

summary(xi)

plot(xi, which=1)

plot(xi, which=2)

plot(xi, which=3)

#### pca

data(expenditures)

p1 <- pcaCoDa(expenditures)

p1

plot(p1)

#### outlier detection

data(expenditures)

oD <- outCoDa(expenditures)

oD

plot(oD)

#### transformations

data(arcticLake)

x <- arcticLake

x.alr <- addLR(x, 2)

y <- addLRinv(x.alr)

addLRinv(addLR(x, 3))

data(expenditures)

x <- expenditures

y <- addLRinv(addLR(x, 5))

head(x)

head(y)

addLRinv(x.alr, ivar=2, useClassInfo=FALSE)

data(expenditures)

eclr <- cenLR(expenditures)

inveclr <- cenLRinv(eclr)

head(expenditures)

head(inveclr)

head(cenLRinv(eclr$x.clr))

require(MASS)

Sigma <- matrix(c(5.05,4.95,4.95,5.05), ncol=2, byrow=TRUE)

z <- isomLRinv(mvrnorm(100, mu=c(0,2), Sigma=Sigma))

## Functions in robCompositions

Name | Description | |

cenLR | Centred logratio coefficients | |

cancerMN | malignant neoplasms cancer | |

int2x2 | Interaction 2x2 table | |

ced | Compositional error deviation | |

gemas | GEMAS geochemical data set | |

educFM | education level of father (F) and mother (M) | |

gjovik | gjovik | |

instw | value added, output and input for different ISIC codes and countries. | |

election | election data | |

machineOperators | machine operators | |

cenLRinv | Inverse centred logratio mapping | |

biplot.factanal | Biplot method | |

alcoholreg | regional alcohol per capita (15+) consumption by WHO region | |

coord | Coordinate representation of compositional tables | |

pcaCoDa | Robust principal component analysis for compositional data | |

corCoDa | Correlations for compositional data | |

manu_abs | Distribution of manufacturing output | |

arcticLake | arctic lake sediment data | |

daFisher | Discriminant analysis by Fisher Rule. | |

adtestWrapper | Wrapper for Anderson-Darling tests | |

perturbation | Perturbation and powering | |

biplot.pcaCoDa | Biplot method | |

bootnComp | Bootstrap to find optimal number of components | |

balances | Balance calculation | |

biomarker | biomarker | |

economy | economic indicators | |

clustCoDa | Cluster analysis for compositional data | |

cancer | hospital discharges on cancer and distribution of age | |

chorizonDL | C-horizon of the Kola data with rounded zeros | |

employment2 | Employment in different countries by Sex, Age, Contract, Value | |

clustCoDa_qmode | Q-mode cluster analysis for compositional parts | |

employment_df | Employment in different countries by gender and status. | |

expendituresEU | mean consumption expenditures data. | |

expenditures | synthetic household expenditures toy data set | |

mcad | metabolomics mcad data set | |

coffee | coffee data set | |

electionATbp | Austrian presidential election data | |

phd_totals | PhD students in the EU (totals) | |

pivotCoord | Pivot coordinates and their inverse | |

compareMahal | Compares Mahalanobis distances from two approaches | |

missPatterns | missing or zero pattern structure. | |

constSum | Constant sum | |

cubeCoord | Coordinate representation of a compositional cube and of a sample of compositional cubes | |

gm | gmean | |

daCoDa | Linear and quadratic discriminant analysis for compositional data. | |

indTab | Independence table | |

gmean_sum | Geometric mean | |

ind2x2 | Independence 2x2 compositional table | |

rdcm | relative difference between covariance matrices | |

orthbasis | Orthonormal basis | |

employment | employment in different countries by gender and status. | |

outCoDa | Outlier detection for compositional data | |

isic32 | ISIC codes by name | |

ilr.2x2 | ilr coordinates in 2x2 compositional tables | |

robCompositions-package | Robust Estimation for Compositional Data. | |

impAll | Replacement of rounded zeros and missing values. | |

govexp | government spending | |

laborForce | labour force by status in employment | |

plot.imp | Plot method for objects of class imp | |

plot.pcaCoDa | Plot method | |

impCoda | Imputation of missing values in compositional data | |

intArray | Interaction array | |

imputeBDLs | EM-based replacement of rounded zeros in compositional data | |

imputeUDLs | Imputation of values above an upper detection limit in compositional data | |

haplogroups | haplogroups data. | |

impRZalr | alr EM-based imputation of rounded zeros | |

impKNNa | Imputation of missing values in compositional data using knn methods | |

precipitation | 24-hour precipitation | |

print.imp | Print method for objects of class imp | |

intTab | Interaction table | |

lifeExpGdp | life expectancy and GDP (2008) for EU-countries | |

tabCoord | Coordinate representation of compositional tables and a sample of compositional tables | |

impRZilr | EM-based replacement of rounded zeros in compositional data | |

lmCoDaX | Classical and robust regression of non-compositional (real) response on compositional predictors | |

stats | Classical estimates for tables | |

ternaryDiagEllipse | Adds tolerance ellipses to a ternary diagram. | |

teachingStuff | teaching stuff | |

pTab | Propability table | |

payments | special payments | |

production | production splitted by nationality on enterprise level | |

rSDev | Relative simplicial deviance | |

summary.imp | Summary method for objects of class imp | |

mortality | mortality and life expectancy in the EU | |

mortality_tab | mortality table | |

ternaryDiagPoints | Add points or lines to a given ternary diagram. | |

nutrients | nutrient contents | |

unemployed | unemployed of young people | |

nutrients_branded | nutrient contents (branded) | |

zeroOut | Detection of outliers of zero-inflated data | |

rSDev.test | Relative simplicial deviance tests | |

rcodes | codes for UNIDO tables | |

variation | Robust and classical variation matrix | |

pfa | Factor analysis for compositional data | |

phd | PhD students in the EU | |

skyeLavas | aphyric skye lavas data | |

socExp | social expenditures | |

trondelagC | regional geochemical survey of soil C in Norway | |

trondelagO | regional geochemical survey of soil O in Norway | |

ternaryDiag | Ternary diagram | |

ternaryDiagAbline | Adds a line to a ternary diagram. | |

SDev | Simplicial deviance | |

GDPsatis | GDP satisfaction | |

addLRinv | Inverse additive logratio mapping | |

adjust | Adjusting for original scale | |

ageCatWorld | child, middle and eldery population | |

alcohol | alcohol consumptions by country and type of alcohol | |

adtest | Anderson-Darling Normality Tests | |

aDist | Aitchison distance | |

addLR | Additive logratio coordinates | |

No Results! |

## Vignettes of robCompositions

## Last month downloads

## Details

Type | Package |

Date | 2019-04-15 |

LinkingTo | Rcpp |

VignetteBuilder | knitr |

License | GPL (>= 2) |

LazyLoad | yes |

LazyData | true |

RoxygenNote | 6.1.1 |

NeedsCompilation | yes |

Packaged | 2019-04-15 16:33:54 UTC; teml |

Repository | CRAN |

Date/Publication | 2019-04-15 17:22:43 UTC |

imports | car , cluster , cvTools , fpc , GGally , kernlab , MASS , mclust , Rcpp , rrcov , sROC , tidyr , VIM , zCompositions |

depends | data.table , e1071 , ggplot2 , pls , R (>= 3.0.0) , robustbase |

suggests | knitr |

Contributors | Alexander Kowarik, Bernhard Meindl, Petra Kynclova, Jan Walach, Veronika Pintar, Jiajia Chen, Dominika Miksova, Kamila Facevicova |

#### Include our badge in your README

```
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```