compositions (version 1.01-1)

print.acomp: Printing compositional data.

Description

Prints compositional objects with appropriate missing encodings.

Usage

## S3 method for class 'acomp':
print(x,...,replace0=TRUE)
## S3 method for class 'aplus':
print(x,...,replace0=TRUE)
## S3 method for class 'rcomp':
print(x,...,replace0=FALSE)
## S3 method for class 'rplus':
print(x,...,replace0=FALSE)

Arguments

x

a compositional object

...

further arguments to print.default

replace0

logical: Shall 0 be treated as "Below detection Limit" with unkown limit.

Value

• An invisible version of x.

Missing Policy

The policy of treatment of zeroes, missing values and values below detecion limit is explained in depth in compositions.missings.

Details

Missings are displayed with an appropriate encoding:

• MAR

{Missing at random: The value is missing independently of its true value.} MNAR{Missing NOT at random: The value is missing dependently of its true value, but without a known systematic. Maybe a better name would be: Value dependen missingness.} BDT{below detection limit (with unspecified detection limit): The value is missing because it was below an unkown detection limit.} {below detection limit (with specified detection limit): The value is below the displayed detection limit. } SZ{Structural Zero: A true value is either bound to be zero or does not exist for structural nonrandom reasons. E.g. the portion of pregnant girls at a boys school.} ERR{Error: An illegal encoding value was found in the object. }

References

Boogaart, K.G. v.d., R. Tolosana-Delgado, M. Bren (2006) Concepts for handling of zeros and missing values in compositional data, in E. Pirard (ed.) (2006)Proceedings of the IAMG'2006 Annual Conference on "Quantitative Geology from multiple sources", September 2006, Liege, Belgium,, S07-01, 4pages, ISBN 978-2-9600644-0-7

See Also

clr,acomp, plot.acomp, boxplot.acomp, barplot.acomp, mean.acomp, var.acomp, variation.acomp, zeroreplace

Examples

data(SimulatedAmounts)
mydata <- simulateMissings(sa.groups5,detectionlimit=0.01,knownlimit=TRUE,MAR=0.05,MNARprob=0.05,SZprob=0.05)
mydata[1,1]<-BDLvalue
print(aplus(mydata))
print(aplus(mydata),digits=3)
print(acomp(mydata))
print(rplus(mydata))
print(rcomp(mydata))