AW: [R] numericDeriv and ecdf

On only ten points, what did you expect ?  Even with 1000
observations, estimating a density is difficult, and has
been the subject of a century of research.  Kernel density
estimates are among the most successful.  For your immediate
application, try  plot(density(rnorm(10)), type="l"), etc.

wait, you misunderstood me!

I'd like to see 10 or 9 points with estimated values of 
*numerical* derivatives according to ecdf output. 
And that's it.

Now look into output of numericDerivative in my example:

[1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
attr(,"gradient")
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    0    0    0    0    0    0    0    0    0     0
 [2,]    0    0    0    0    0    0    0    0    0     0
 [3,]    0    0    0    0    0    0    0    0    0     0
 [4,]    0    0    0    0    0    0    0    0    0     0
 [5,]    0    0    0    0    0    0    0    0    0     0
 [6,]    0    0    0    0    0    0    0    0    0     0
 [7,]    0    0    0    0    0    0    0    0    0     0
 [8,]    0    0    0    0    0    0    0    0    0     0
 [9,]    0    0    0    0    0    0    0    0    0     0
[10,]    0    0    0    0    0    0    0    0    0     0

What could you say now?

With kind regards,
Valery A.Khamenya
---------------------------------------------------------------------------
Bioinformatics Department
BioVisioN AG, Hannover

On only ten points, what did you expect ?  Even with 1000
observations, estimating a density is difficult, and has
been the subject of a century of research.  Kernel density
estimates are among the most successful.  For your immediate
application, try  plot(density(rnorm(10)), type="l"), etc.

wait, you misunderstood me!

I'd like to see 10 or 9 points with estimated values of
*numerical* derivatives according to ecdf output.

An empirical CDF is a step function: it does not have a derivative at the 
jump points, and has a zero derivative everywhere else.

What is this function `numericDerivative': do you mean `numericDeriv'?
If so, it seems to be intended for differentiable functions, and
calculates one-sided derivatives.  In your example the one-sided 
derivatives are all zero.

z <- 0
numericDeriv(quote(e(x-z)),"z");