On Thu, 7 Feb 2008, Tyler Smith wrote:
On 2008-02-07, Birgit Lemcke <[EMAIL PROTECTED]> wrote:
Am 06.02.2008 um 21:00 schrieb Tyler Smith:
My dataset contains variables of the classes factor and numeric. Is
there another function that is able to handle this?
The numeric variables are fine. The factor variables may have to be
recoded into dummy binary variables, I'm not sure if lda() will deal
with them properly otherwise.
But aren´t binary variables also factors? Or is there another
variable class than factor or numeric?
Do I have have to set the classe of the binaries as numeric?
There is no binary class in R, so you would have to use a numeric
field. For example:
Then what do you consider the logical type to be?
(Strictly it is not binary because of NAs, but it is used for binary
variables in model formulae.)
| sample | factor_1 |
|--------+----------|
| A | red |
| B | green |
| C | blue |
becomes:
| sample | dummy_1 | dummy_2 |
|--------+---------+---------|
| A | 1 | 0 |
| B | 0 | 1 |
| C | 0 | 0 |
R can deal with dummy_1 and dummy_2 as numeric vectors. The details
should be explained in a good reference on multivariate statistics
(I'm looking at Legendre and Legendre (1998) section 1.5.7 and 11.5).
The issue is rather a statistical one: the theory behind LDA assumes
continuous variables, indeed a multivariate normal distribution. You can
apply LDA to binary explanatory variables, but there are much more
appropriate methods (as indeed there are for factor explanatory
variables).
HTH,
Tyler
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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