Coordinate representation of compositional tables and a sample of compositional tables
tabCoord computes a system of orthonormal coordinates of a compositional table. Computation of either pivot coordinates or a coordinate system based on the given SBP is possible.
tabCoordWrapper: For each compositional table in the sample tabCoordWrapper
computes a system of orthonormal coordinates and provide a simple descriptive analysis.
Computation of either pivot coordinates or a coordinate system based on the given SBP is possible.
tabCoord( x = NULL, row.factor = NULL, col.factor = NULL, value = NULL, SBPr = NULL, SBPc = NULL, pivot = FALSE, print.res = FALSE ) tabCoordWrapper( X, obs.ID = NULL, row.factor = NULL, col.factor = NULL, value = NULL, SBPr = NULL, SBPc = NULL, pivot = FALSE, test = FALSE, n.boot = 1000 )
x |
a data frame containing variables representing row and column factors of the respective compositional table and variable with the values of the composition. |
row.factor |
name of the variable representing the row factor. Needs to be stated with the quotation marks. |
col.factor |
name of the variable representing the column factor. Needs to be stated with the quotation marks. |
value |
name of the variable representing the values of the composition. Needs to be stated with the quotation marks. |
SBPr |
an I-1\times I array defining the sequential binary partition of the values of the row factor, where I is the number of the row factor levels. The values assigned in the given step to the + group are marked by 1, values from the - group by -1 and the rest by 0. If it is not provided, the pivot version of coordinates is constructed automatically. |
SBPc |
an J-1\times J array defining the sequential binary partition of the values of the column factor, where J is the number of the column factor levels. The values assigned in the given step to the + group are marked by 1, values from the - group by -1 and the rest by 0. If it is not provided, the pivot version of coordinates is constructed automatically. |
pivot |
logical, default is FALSE. If TRUE, or one of the SBPs is not defined, its pivot version is used. |
print.res |
logical, default is FALSE. If TRUE, the output is displayed in the Console. |
X |
a data frame containing variables representing row and column factors of the respective compositional tables, variable with the values of the composition and variable distinguishing the observations. |
obs.ID |
name of the variable distinguishing the observations. Needs to be stated with the quotation marks. |
test |
logical, default is |
n.boot |
number of bootstrap samples. |
tabCoord
This transformation moves the IJ-part compositional tables from the simplex into a (IJ-1)-dimensional real space isometrically with respect to its two-factorial nature. The coordinate system is formed by two types of coordinates - balances and log odds-ratios.
tabCoordWrapper: Each of n IJ-part compositional tables from the sample is with respect to its two-factorial nature isometrically transformed from the simplex into a (IJ-1)-dimensional real space. Sample mean values and standard deviations are computed and using bootstrap an estimate of 95 % confidence interval is given.
Coordinates |
an array of orthonormal coordinates. |
Grap.rep |
graphical representation of the coordinates. Parts denoted by |
Ind.coord |
an array of row and column balances. Coordinate representation of the independent part of the table. |
Int.coord |
an array of OR coordinates. Coordinate representation of the interactive part of the table. |
Contrast.matrix |
contrast matrix. |
Log.ratios |
an array of pure log-ratios between groups of parts without the normalizing constant. |
Coda.table |
table form of the given composition. |
Bootstrap |
array of sample means, standard deviations and bootstrap confidence intervals. |
Tables |
Table form of the given compositions. |
Kamila Facevicova
Facevicova, K., Hron, K., Todorov, V. and M. Templ (2018) General approach to coordinate representation of compositional tables. Scandinavian Journal of Statistics, 45(4), 879–899.
###################
### Coordinate representation of a CoDa Table
# example from Fa\v cevicov\'a (2018):
data(manu_abs)
manu_USA <- manu_abs[which(manu_abs$country=='USA'),]
manu_USA$output <- factor(manu_USA$output, levels=c('LAB', 'SUR', 'INP'))
# pivot coordinates
tabCoord(manu_USA, row.factor = 'output', col.factor = 'isic', value='value')
# SBPs defined in paper
r <- rbind(c(-1,-1,1), c(-1,1,0))
c <- rbind(c(-1,-1,-1,-1,1), c(-1,-1,-1,1,0), c(-1,-1,1,0,0), c(-1,1,0,0,0))
tabCoord(manu_USA, row.factor = 'output', col.factor = 'isic', value='value', SBPr=r, SBPc=c)
###################
### Analysis of a sample of CoDa Tables
# example from Fa\v cevicov\'a (2018):
data(manu_abs)
### Compositional tables approach,
### analysis of the relative structure.
### An example from Facevi\v cov\'a (2018)
manu_abs$output <- factor(manu_abs$output, levels=c('LAB', 'SUR', 'INP'))
# pivot coordinates
tabCoordWrapper(manu_abs, obs.ID='country',
row.factor = 'output', col.factor = 'isic', value='value')
# SBPs defined in paper
r <- rbind(c(-1,-1,1), c(-1,1,0))
c <- rbind(c(-1,-1,-1,-1,1), c(-1,-1,-1,1,0),
c(-1,-1,1,0,0), c(-1,1,0,0,0))
tabCoordWrapper(manu_abs, obs.ID='country',row.factor = 'output',
col.factor = 'isic', value='value', SBPr=r, SBPc=c, test=TRUE)
### Classical approach,
### generalized linear mixed effect model.
## Not run:
library(lme4)
glmer(value~output*as.factor(isic)+(1|country),data=manu_abs,family=poisson)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.