NA, Inf, -Inf, NaN would give you 4 possibilities and is.finite would
check if its any of them:
x - c(1, NA, 2, Inf, 3, -Inf, 4, NaN, 5)
is.finite(x)
[1] TRUE FALSE TRUE FALSE TRUE FALSE TRUE FALSE TRUE
You might need to map them all to NA before using it with various
functions depending
I can think of a few solutions, none perfect.
* You could have a master dataset that has the
missing value codes you want, and a dataset that
you use which is a copy of it with real NA's in it.
* You could add an attribute that gives the types
of missing values in the various positions. The
Patrick Burns wrote:
I can think of a few solutions, none perfect.
* You could have a master dataset that has the
missing value codes you want, and a dataset that
you use which is a copy of it with real NA's in it.
* You could add an attribute that gives the types
of missing values in the
...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Frank E Harrell Jr
Sent: Sunday, February 14, 2010 9:39 AM
To: Patrick Burns
Cc: r-help@r-project.org; john.macin...@ed.ac.uk
Subject: Re: [R] Multiple missing values
Patrick Burns wrote:
I can think of a few solutions, none
John wrote:
...
Does anyone know, or know documentation that describes, how to declare
multiple values in R as missing that does not involve coding them as NA? I
wish to be able to treate values as missing, while still retaining codes
that describe the reason for the value being missing.
I
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