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The missing codes can be replace with arbitrary value e.g. IEEE numbers and viceversa through this interface.
gsi.recodeM2C(x,y=x,BDL,SZ,MAR,MNAR,NMV) gsi.recodeC2M(x,y=x,na,nan,ninf,inf,neg,zero,pos) gsi.recodeM2Clean(x,y=x,BDL=NaN,SZ=NaN,MAR=NaN,MNAR=NA,NMV) gsi.cleanR(x)
y with entries replaced. gsi.cleanR replaces all improper numbers with 0.
the dataset having missings or IEEE numbers
a dataset of similar shape, where the replacment should take place
value to replace for BDL
value to replace for SZ
value to replace for MAR
value to replace for MNAR
value to replace for NMV
value to replace for NA
NA
value to replace for NaN
NaN
value to replace for -Inf
-Inf
value to replace for Inf
Inf
value to replace for numbers with x<0
x<0
value to replace for numbers with x==0
x==0
value to replace for numbers with x>0
x>0
K.Gerald v.d. Boogaart http://www.stat.boogaart.de
This functions are used internally to transform the different types of missings correctly.
compositions.missing
#gsi.plain(acomp(c(12,3,4)))
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