sci.stat.math Google Group

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Re: the distribution of the ratio of two binomial random variables?

koop...@sfu.ca (Ray Koopman) — Thu, 26 Nov 2009 08:59:29 UT

Add a third property: Swapping p1 and p2 reverse the pmf
(i.e., reflects it thru Z = 1/2).

Re: the distribution of the ratio of two binomial random variables?

koop...@sfu.ca (Ray Koopman) — Thu, 26 Nov 2009 07:56:45 UT

If you exclude (0,0) from the joint distribution of (X,Y), which are
otherwise independent binomials with the same n but possibly different
p's, and let Z = X/(X+Y), then two things are immediately apparent
from looking at a few plots:
1. The values that Z can have are symmetrically placed in [0,1].

Re: Mechanical generation of random bit sequences

robertwess...@yahoo.com (robertwessel2@yahoo.com) — Thu, 26 Nov 2009 06:55:18 UT

A PS/2 style keyboard/mouse UART runs asynchronously from the CPU.
And you're measuring the nanosecond arrival of the keystroke at the
program, which depends on exactly when the key is hit by the user,
when the keystroke is sent by the keyboard, when the keystroke is
received by the UART, when the interrupt is received by the CPU, when

Re: Mechanical generation of random bit sequences

gor...@hammy.burditt.org (Gordon Burditt) — Thu, 26 Nov 2009 06:32:33 UT

Does it really matter whether the counter on the PC is running at
1GHz, when the keyboard characters on an AT-style keyboard are
clocked in at a frequency more like 20-30KHz? A single character
(scan code) is 11 bits, although some keystrokes are more than one
character. (This may not be an issue on USB keyboards, or maybe

Re: Mechanical generation of random bit sequences

robertwess...@yahoo.com (robertwessel2@yahoo.com) — Thu, 26 Nov 2009 05:31:03 UT

Yes it does. On x86 the hardware timestamp counter is specifically
defined to be a count of the CPU's clock ticks. So a 1GHz processor
will increment the TSC on billion time each second. And it's
specifically defined *not* to do what you suggest, which is to add a
larger quantity at longer intervals.

Re: regression question

he...@alumni.brown.edu (Greg Heath) — Thu, 26 Nov 2009 04:28:42 UT

A very quick search found
[link]
Hope this helps,
Greg

Re: Mechanical generation of random bit sequences

unruh-s...@physics.ubc.ca (Unruh) — Thu, 26 Nov 2009 04:13:02 UT

So what? That does not mean that that the system has nanosecond resolution. You
could put that time into a 128 byte word, and get a resolution of atoseconds. But
the reading of the clock does not give you that accuracy. Ie if you get nanosecond
resultion but the clock always gives 1 second accuracy, that extra 30 bits are

Re: Correlation and Observations with Zero Value

knight_arm...@yahoo.com (Graham Ashe) — Thu, 26 Nov 2009 04:05:04 UT

Yes. I suppose as long as the sample mean <> 0, the correlation value, however low and/or insignificant, is still valid.
Even so, I'd like to know whether many zero values for observations in a sample compromise the accuracy of correlations calculated using that sample. I'm inclined to think it does.

Re: regression question

he...@alumni.brown.edu (Greg Heath) — Thu, 26 Nov 2009 04:06:11 UT

The RBF is a universal aprroximator. Therefore it will work.
However, the question really is "How well will it work?"
In general whether an MLP or a RBF works better depends
on the data.
Unfortunately, the MATLAB function newrb is not the best
software available. I have a considerable number of posts

Re: Seduced by goodness of fit

he...@alumni.brown.edu (Greg Heath) — Thu, 26 Nov 2009 03:39:10 UT

I agree.
Unfortunately, however, many times the attempt at
modelling comes at a time when the modeler doesn't
have a sufficient understanding of the phenomena
and/or doesn't have a preponderance of data.
In the latter case cross-validation, bootstrapping,
regularization and randomizing inputs are useful.

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Re: Correlation and Observations with Zero Value

he...@alumni.brown.edu (Greg Heath) — Thu, 26 Nov 2009 02:27:41 UT

Can the samples be considered random draws from a population
defined over an interval for which zero is an interior point?
Greg

Re: Is Huber Estimator IRLS Weight Wrong in Literature?

aruzin...@general-cathexis.com (aruzinsky) — Thu, 26 Nov 2009 02:02:21 UT

Correction:
rho(et) = (rho(et-1)/(et-1)^2)*et^2 at convergence.

Is Huber Estimator IRLS Weight Wrong in Literature?

aruzin...@general-cathexis.com (aruzinsky) — Thu, 26 Nov 2009 01:58:56 UT

See [link]. I see this
often in literature but
I get
Wh(e) = 1/2 for |e| <= k
Wh(e) = k/|e| - ( (k/e)^2 )/2 for |e| > k
The derivation is simply rho(e)/e^2 because, at convergence, et = et-1
therefore the weighted error (rho(et)/et^2)*(et-1)^2 = rho(et) where t

Correlation and Observations with Zero Value

knight_arm...@yahoo.com (Graham Ashe) — Thu, 26 Nov 2009 00:56:07 UT

In measuring the correlation (Pearson, Spearman) between two samples, what is the maximum number or proportion of observations within each sample that can have a '0' value? I'm asking because some of my samples result in many observations having a '0' value. I'm concerned too many of these will influence the reliability of the correlation being measured.

Re: the distribution of the ratio of two binomial random variables?

perfr...@gmail.com (per) — Wed, 25 Nov 2009 22:57:25 UT

i would like to assume that X(X+Y) >= 0, meaning X+Y >= 1. under that
assumption, is there a form for this distribution?

Re: Mechanical generation of random bit sequences

robertwess...@yahoo.com (robertwessel2@yahoo.com) — Wed, 25 Nov 2009 21:58:49 UT

It sounds like you're using the wrong timer to measure the interval
between keystrokes. The 56/57/58 numbers sound like you may be
picking up something with timing based on the old DOS 18.2Hz timer,
the 28/29 sounds like half that for some reason. At least the former
were the defaults for all DOS, Win3.x and Win9x, and that effectively

Re: Mechanical generation of random bit sequences

robertwess...@yahoo.com (robertwessel2@yahoo.com) — Wed, 25 Nov 2009 21:46:18 UT

It’s trivial to get nanosecond-scale resolution timings on many
processors. On (semi-modern) x86, for example, you can read the time
stamp counter, which basically gives you a 64 bit number of clock
ticks since the CPU was powered on. So on a 2GHz process, each count
is half a nanosecond.
Simply looking at the low bits of that time captures a great deal of

Re: Seduced by goodness of fit

rodrodrod...@hotmail.com (Rod) — Wed, 25 Nov 2009 20:58:32 UT

Well said.

Seduced by goodness of fit

noem...@home.org (root) — Wed, 25 Nov 2009 19:33:15 UT

There is a current thread running in this group
under the heading "a regression question". Suggestions
abound for combinations of independent variables to
fit 45 data points, with success being measured
by goodness of fit, and not whether any sense can
be made out of such combinations.
Regression is a very powerful tool and R**2 can

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Re: Mechanical generation of random bit sequences

mok-kong.s...@t-online.de (Mok-Kong Shen) — Wed, 25 Nov 2009 15:32:54 UT

That seems all highly magnificent, though I personally couldn't
believe that in 10 seconds one could via keystroke generate 1911 bits
of entropy. As I said, if this is so, then one wouldn't have to bother
to consider other means of getting entropy, which, very interestingly,
you yourself also die consider in the posts. (I questioned in a post

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Re: regression question

icyst...@hotmail.com (icystorm) — Wed, 25 Nov 2009 13:48:54 UT

Greg, do you think this type of RBF Gaussian function could work?
[link]
If so, I will examine this approach tonight.
Cheers,
Joseph

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Re: Mechanical generation of random bit sequences

bernh...@bksys.at (Bernhard Kuemel) — Wed, 25 Nov 2009 11:39:51 UT

It's better to know, than to believe, especially in cryptography. Maybe
you can understand it this way:
Say you have a RNG which gives you numbers from 0-7. You can translate
these numbers to 3 random bits. Now, I haven't told you, how you get the
numbers from the RNG. It produces a random voltage in the range of 0-8V.

Re: Mechanical generation of random bit sequences

mok-kong.s...@t-online.de (Mok-Kong Shen) — Wed, 25 Nov 2009 10:23:09 UT

I was simply astonished about the extraordinary large rate of the
entropy generation he claimed to be achievable with his methodology.
Much like I would greatly wonder, if a researcher in agriculture
would claim that he had succeeded to grow apples each weighing more
than 3 kg. I don't know, but maybe indeed nothing is impossible under

Re: Mechanical generation of random bit sequences

bernh...@bksys.at (Bernhard Kuemel) — Wed, 25 Nov 2009 10:24:48 UT

Re: regression question

he...@alumni.brown.edu (Greg Heath) — Wed, 25 Nov 2009 10:00:22 UT

The point I was trying to make is that perhaps the variance in the
data is not adequately represented by the second order polynomial.
However, instead of trying to improve the representation by using a
higher order polynomial, a change to a universal approximator
model like the MLP sum of tanh sigmoids or Radial Basis Function

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Re: Mechanical generation of random bit sequences

robertwess...@yahoo.com (robertwessel2@yahoo.com) — Wed, 25 Nov 2009 05:37:38 UT

It's the *timing* of the single keystroke that yields a bunch of
entropy, not what's typed.

Re: prior information in mean and variance in regression

richardsta...@comcast.net (Richard Startz) — Wed, 25 Nov 2009 04:44:53 UT

On Tue, 24 Nov 2009 16:59:22 -0800 (PST), soms <soms.sha...@gmail.com>
wrote:
The mean and variance of y are almost irrelevant to regression
analysis. Further, there is no reason why the mean or variance of y
should be the same in different samples. Both depend on f(x).
-Dick Startz

Re: prior information in mean and variance in regression

imageanal...@mailinator.com (ImageAnalyst) — Wed, 25 Nov 2009 03:34:37 UT

I still don't understand. The mean of your small sample is what it
is. You can't change it. Like I said, it is what it is. If you make
it something different, then it's not the actual mean anymore. Yes,
it won't equal the mean of your much larger sample set but that's the
way it goes. You just have to live with it. That's just basic

Re: prior information in mean and variance in regression

soms.sha...@gmail.com (soms) — Wed, 25 Nov 2009 03:19:14 UT

Sorry, for not unclear statements.
Yes, I have a small set of (x,y) data for regression. But, I know the
distribution of y i.e. mean and variance from large sample set (a
prior knowledge from some source). Now I would like to develop a
regression model for the available small set of (x,y) data in such a

Re: regression question

icyst...@hotmail.com (icystorm) — Wed, 25 Nov 2009 03:04:57 UT

I think that beginning to work on a problem is never a waste of time.
I may never develop a solution, but I will learn more about the
problem during the journey, and I will document the things I learn.
The ADCIRC and SLOSH models do use detail beyond google maps. Their
respective topgraphical resolutions are based on LIDAR measurements.

Re: regression question

icyst...@hotmail.com (icystorm) — Wed, 25 Nov 2009 02:48:17 UT

Thanks kindly for your ideas and suggestions, Greg.
I must have ran 1000 trials over the past few days using every
combination imaginable.
I'm starting to examine the idea of sorting by the size parameter (X1)
and breaking the data down into three sets of small, medium, and large
hurricanes. That seems to have some promise.

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Re: regression question

he...@alumni.brown.edu (Greg Heath) — Wed, 25 Nov 2009 02:16:06 UT

-----SNIP
Different Inputs
Overfitting
-Regularization
-Cross Validation
Model Interpretation
Neural Networks
Re only the latter:
I designed 100 feedforward multilayer perceptrons
(took ~ 71 sec) to consider typical FFMLP sum of
tanh models. In matrix notation
y = B20 + B2*tanh(B10+B1*X).
I ran 25 random weight initialization trials for

Re: prior information in mean and variance in regression

imageanal...@mailinator.com (ImageAnalyst) — Wed, 25 Nov 2009 02:15:51 UT

I'm not sure I understand, but I'm not a statistician. If you know
the "true" values (or at least more accurate ones from a larger
sample), why not just use them if you want to? Otherwise you have the
sample statistics. Which do you want to use? Are you looking for
some kind of equation that gives error as a function of the number of

prior information in mean and variance in regression

soms.sha...@gmail.com (soms) — Wed, 25 Nov 2009 00:59:22 UT

Greetings !
I have a small sample available for regression analysis of the form y=f
(x). As the sample size increases the regression equation based on
small sample would not be appropriate.
We have prior knowledge about the mean and variance of y of larger
sample size. How can we use these information to update regression

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Re: Mechanical generation of random bit sequences

mok-kong.s...@t-online.de (Mok-Kong Shen) — Tue, 24 Nov 2009 20:13:22 UT

Sorry, I simply can't believe that anybody with a single keystroke
could give rise to 13 or 20 bits of entropy. Sorry.
M. K. Shen

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Re: Do you think this evidence is reassuring about the nonviolence of schizopherenics?

aruzin...@general-cathexis.com (aruzinsky) — Tue, 24 Nov 2009 17:49:50 UT

No, the heart of the issue is the making of bad decisions based on
false perception. To use a perception to make a decision requires a
degree of conviction that the perception is correct. Without false
conviction, there is no problem.
No, I predict much more than explain or rationalize. If my
predictions are wrong, I adjust my model of reality. If I suspect

sci.stat.math Google Group

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Re: the distribution of the ratio of two binomial random variables?

Re: the distribution of the ratio of two binomial random variables?

Re: Mechanical generation of random bit sequences

Re: Mechanical generation of random bit sequences

Re: Mechanical generation of random bit sequences

Re: regression question

Re: Mechanical generation of random bit sequences

Re: Correlation and Observations with Zero Value

Re: regression question

Re: Seduced by goodness of fit

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Re: Correlation and Observations with Zero Value

Re: Is Huber Estimator IRLS Weight Wrong in Literature?

Is Huber Estimator IRLS Weight Wrong in Literature?

Correlation and Observations with Zero Value

Re: the distribution of the ratio of two binomial random variables?

Re: Mechanical generation of random bit sequences

Re: Mechanical generation of random bit sequences

Re: Seduced by goodness of fit

Seduced by goodness of fit

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Re: regression question

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Re: Mechanical generation of random bit sequences

Re: prior information in mean and variance in regression

Re: prior information in mean and variance in regression

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Re: regression question

Re: regression question

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