[R] R-help Digest, Vol 35, Issue 24
spencer.graves at pdf.com
Wed Jan 25 03:01:46 CET 2006
Dear Mr. Chamberlain:
You asked for free consulting, and as near as I can tell, you got
pretty good advice. Now you complain that you don't like the packaging.
If you can't stand the heat, get out of the kitchen.
Professor Brian Ripley has an international reputation based on solid
contributions to human knowledge over many years. He is an expert in
statistical science, not diplomacy. Professor Ripley has been
incredibly generous in donating substantial portions of his time for
many years both to help make R what it is today and to answering
questions on this listserve. I think he deserves a great deal of
respect for not only the time he has devoted to this but to how much he
has achieved with that time.
What would you like him to do as a result of your email? Retire?
Stop contributing to this listserve and to the R project more generally?
I sincerely hope he does not consider such. It would be a great loss
to humanity if he did.
Mr. Chamberlain, if English (or as Prof. Ripley might say,
"American") is your mother tongue, then your deplorable lack of skill in
its use raises serious questions about the standard of academic
excellence at the University of Colorado, which I had previously thought
was a great university and the finest Colorado had to offer. Of course,
if English is a second language for you, then I would not complain.
Rather, I would be humbled and honored that you chose to meet the rest
of the world in my native tongue. Another question: The web lists you
as a senior in psychology. Have you learned anything in your study of
psychology? I would think that psychology students should meet a much
higher standard for social skills and communications than you have
displayed today. Would you like me to forward your correspondence to,
say, the editor of the Flatiron News there in Boulder or Prof. W. Edward
Craighead, the chair of the Psychology Dept., asking if a degree from
the once-great University of Colorado is supposed to imply that the
degree holder meets any standard for academic excellence in comportment
and the use of language?
Keith.Chamberlain at colorado.edu wrote:
> Dear Prof Ripley,
> First of all, unless you are an english professor, then I do not think you have
> any business policing language. I'm still very much a student, both in R, and
> regarding signal analysis. My competence on the subject as compared too your
> own level of expertise, or my spelling for that matter, may be a contension for
> you, but it would have been better had you kept that opinion too yourself. There
> are plenty of other reasons besides laziness or carelessness that people will
> consistently error in language use, such as learning disorders, head injuries,
> and/or vertigo.
> On the contrary, I am aware of the definition of a periodogram, and I know what
> the unnormalized periodogram in the data I presented looks like. Spec.pgram()
> is actually normalized too something, because it's discrete integral is not
> well above the SS amplitude of the signal it computed the periodogram for. In
> other words, the powers are not in units of around 4,000, which the peak would
> be if the units were merely the modulus squared of the Fourier coeficients of
> the data I presented. Alas, the modulus squared of the Fourier coeficients IS
> the TWO SIDED unnormalized periodogram, ranging from [-fc, fc] | fc=nyquist
> critical frequency. The definition of the ONE SIDED periodogram IS the modulus
> squared of the Fourier coeficients ranging over [0, fc], but since the function
> is even, data points in (0, fc) non-inclusive, need to be multiplied by 2. Thus
> is according too the "definition" given by Press, et al (1988, 1992, 2002, c.f.
> cp 12 & 13). I'm assuming that R returns an FFT in the same layout as Press, et
> al describe.
> Press, et al. are also very clear about the existence of far too many ways of
> normalizing the periodogram too document, which they stated before delving into
> particularly how they normalized to the mean squared amplitude of the signal
> that the periodogram was computed from. In the page before, and perhaps this is
> where some of the confusion arises from, they document the calculations for MS
> and SS amplitudes and "time integral squared amplitude" of the signal in the
> "time" domain, not the frequency domain. The page after that, their example
> only shows how to normalize a periodogram so its sum is equal too the MS
> amplitude. In short, but starting from SS amplitude:
> a). sum(a[index=(1:N) or t=(0:N-1)]^2) = SS amplitude calculated in time domain
> b). 1/N * sum(Mod(fft[-fc:fc])^2) = two sided periodogram that sums too the SS
> c). Same as b but over the range [0, fc], and (0, fc) multiplied by 2 is the one
> sided periodogram, also sums too the SS amplitude
> For MS amplitude, the procedures are identical, only the time domain is divided
> by N, and the frequency domain figures are divided by N^2 instead of N.
> When the periodogram is in power per unit time, as in the above, so that the
> power is interpretable at N/2+1 independent frequencies, it is a normalized
> periodogram. spec.pgram() IS normalized, I just do not know what it's
> normalized too because I can not seem to get spec.pgram to stop tapering (at
> which point the normalization should be dead on, not just "close").
> By the way, "normalized" does not automatically mean anything unless "to what"
> is stated. I could normalize something arbitrarily to the number of tics on my
> dogs back side, and still call it normed, or erroneously refer too it as
> unnormed. If "normalized" is suposed to mean something specific, then I am
> confident that more than 90% of undergraduates are not familiar with what the
> term "should" mean. Stats and coding and using programs are a human endeavor.
> This human seems to have made meaning out of terms differently than what those
> who wrote the documentation seem to have intended. Only, I do not know where
> the documentation or my understanding may have been missled (R docs, Numerical
> Recipes, or any other source I looked at since I started).
> First, please look up `too' in your dictionary.
> Second, please study the references on the help page, which give the
> details. That is what references are for! The references will also
> answer your question about the reference distribution.
> The help page does not say it is `normalized' at all: it says it computes
> the peridogram, and you seem unaware of the definitions of the latter (and
> beware, there are more than one).
> On Tue, 24 Jan 2006, Keith Chamberlain wrote:
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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