Dear R users,

I am trying to conduct a simprof analysis to determine if groups of objects
form statistically significant clusters.

The variables that I am using are a mixture of categorical, ordered, and
numerical. I am therefore using Gower's distance for this analysis. Below
is the code with my commentary.


### Below specifies the columns of the larger dataframe to use to calculate
### distances among the objects in my dataset

Fv<-F[,8:31]

### I feed the function below into the code for conducting simprof analyses
to
###  specify what distance measure to use, i.e., to what "method.distance"
is ###  equal.

G.Matrix <- function (Fv) FD::gowdis(Fv, ord = "metric")

### I then do the analysis.

Fsp <- simprof(Fv, num.expected=1000, num.simulated=999,
                method.cluster="average", method.distance=G.Matrix,
                alpha = 0.01, silent=FALSE, increment=100)

After that, I get the following error message:

                   Error in FD::gowdis(Fv, ord = "metric") :
                     x is not a dataframe or a numeric matrix

So it appears that the data used in a simprof analysis has to be numeric
(which mine is not). The code structure does work when I use a dataframe
with purely numeric data. So my questions are:

1) Is there a way in R to run a Simprof analysis on data that is not all
numerical?

2) If not, why? That is, why can't simprof analyses be done on
non-numerical data. I read Clarke and Gorley's explanation in their PRIMER
manual of Simprof analyses and I was unclear from their description as to
why Simprof analyses cannot be conducted on non-numerical data.

Finally, any suggested readings on the topic would be greatly appreciated.

Thanks in advance for any assistance.

Sincerely,

-- 
Basil V. Iannone III
University of Illinois at Chicago
Department of Biological Sciences (MC 066)
845 W. Taylor St.
Chicago, IL  60607-7060
Email: bianno2@uic.edu
Phone: 312-355-0987
Fax: 312-413-2435
http://www2.uic.edu/~bianno2

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