Thank you for pointing me to ?dissimilarity.object. I now see that N = Nominal
(factor) and I = Interval scaled (numeric).

Regards.


On Sun, Feb 24, 2013 at 2:36 PM, Peter Ehlers <ehlers@ucalgary.ca> wrote:

> On 2013-02-24 07:57, Joanna Papakonstantinou wrote:
>
>> I am using the iris dataset that contains mixed variables (some columns
>>> are numeric and some categorical).
>>>
>>>  iris
>>>>
>>>      Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
>>> 1            5.1         3.5          1.4         0.2     setosa
>>> 2            4.9         3.0          1.4         0.2     setosa
>>> 3            4.7         3.2          1.3         0.2     setosa
>>> 4            4.6         3.1          1.5         0.2     setosa
>>> .
>>> .
>>> .
>>>
>>
>>  I am trying to use the Gower metric so that I may specify that some
>>> columns contain categorical data.
>>>
>>>> iris.clust<-daisy(iris, metric = "gower", stand = FALSE, type =
>>>> list(factor="Species"))
>>>>
>>> But it is saying that the types= I, I, I, I, N
>> so obviously it is not reading the variable types correctly.
>>
>
> I don't know why you say that. Look at ?dissimilarity.object to see
> what 'I' and 'N' mean.
>
> If you read the help page for ?daisy carefully, you'll see that your
> command is equivalent to
>
>   iris.clust(iris)
>
> i.e. you need not specify the metric etc.
> BTW, your specification of 'type' indicates that you may have
> looked at the help page a bit too hastily.
>
>
>
>> Could someone please tell me how to specify the variable types correctly?
>>
>> Thank you.
>> Joanna
>>
>
> Peter Ehlers
>
>


-- 
******************************************************************


*Joanna Papakonstantinou, Ph.D.*

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