Help with manipulation of matrix object

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Hi, Jeremy!
... I have a matrix, measuring m X n. An example matrix will be this:
... [snip] ...
What I want to do is actually statistical manipulation of this matrix. 
To be more precise, I want to calculate the probability of each value, 
based on the assumption of a normal distribution, based on the row mean 
and standard deviation.
Hm, I think you have to be more precise since the probability to observe a 
specific value under the assumption of a continuous distribution (e.g., 
the normal distribution) is zero -- always.

And you presumably do not want the first column to be included in the 
calculation of the median, the sd, and finally the probability, do you?

However, if I understand correctly, you could maybe proceed as follows: 
With
row.median <- apply( sample[, -1], 1, median)
row.sd <- apply( sample[, -1], 1, sd)
you could standardize the rows of your matrix by
rowwise.standardized.sample <- (sample[, -1] - row.median) / row.sd
(utilizing the way matrices and vectors are handled in arithmetic 
expression), and then use relations within the family of normal 
distributions to compute density or cumulative probability values by
dnorm( rowwise.standardized.sample) / row.sd
pnorm( rowwise.standardized.sample)
Hth  --  Gerrit
For example,
sample[2,2] = 4.37914 <- This value is derived from the matrix, row 2
column 2.
To calculate the median (which i am using in place of the mean in the
normal distribution), I know I have to use the apply function;

the same goes for the standard deviation:

sd<-apply(sample,1, sd)
With both the median and the sd in hand, I want to write the probability of
observing the value reported at sample[2,2]

I can do this manually, but as the dataframe gets larger and larger, this
becomes more time consuming; and furthermore, I wish to write the
probability as a matrix of the exact same dimensions, except that instead
of a matrix reporting the values I now have a matrix of reporting the
probabilities.

The median and sd is calculated for each row.

Any help/ thoughts on this will be greatly appreciated!

Jeremy

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