Thanks for your help. It is working now.
Marc.
Gavin Simpson wrote:
> On Thu, 2008-01-10 at 10:48 +0000, Marc Moragues wrote:
>
>> Hi,
>>
>> I am trying to calculate a distance matrix on a binary data frame using
>> dist.binary() {ade4}. This is the code I run and the error I get:
>>
>>
>>> sjlc.dist <- dist.binary(as.data.frame(data), method=2) #D = (a+d) /
>>>
>> (a+b+c+d)
>> Error in if (any(df < 0)) stop("non negative value expected in df") :
>> missing value where TRUE/FALSE needed
>>
>> I don't know if the problem are the missing values in my data. If so how
>> can I handle them?
>>
>
> Marc,
>
> Take a look at distance in package analogue and method = "mixed" which
> implements Gower's general dissimilarity coefficient for mixed data. It
> can deal quite happily with binary data and where there is missing-ness.
> Binary data are handled through a simple matching coefficient, 1 if
> variable i present in both samples, 0 otherwise, and then summed over
> all variables i. You should probably read up on how the missing-ness is
> handled with this method and what properties the resulting dissimilarity
> has.
>
> Note that distance() outputs full dissimilarity matrices. To get
> something to plug into functions that require a dist object, just use
> as.dist() on the output from distance().
>
> HTH
>
> G
>
>
>> Thank you,
>> Marc.
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