The only thing THAT MATTERS
Luis A. Afonso
***** Date: Nov 14, 2007 2:16 PM
Author: John Smith
Subject: Re: Turn a uniform number to normal random numbers
Luis,
You never bothered to finish discussing your last error before you committed another one. Please pay attention.
On Nov 11, 4:22 am
You wrote"From this values we obtain the CONFIDENCE INTERVALS of the two-tailed tests relative to the probabilities 99%, 98%, 95% the parameter be inside." Either the parameter is INSIDE or OUTSIDE. The probability that the parameter is inside is either 100% or 0%. Same for the probability that the parameter is outside. Please defend your assertion that there can be a 99% probability that a parameter is inside the interval. John
********************
My response
In this special matter (and others) Jonh Smith only sas nonsense. THE INSIDE-OUTSISE THEORY is STUPID in more than one aspect.
*** The explanation I repeat below
John Smith doe not LOOSE AN OPPORTUNITY to show us how IGNOEANT (and STUPID) is.*****
****
The only thing THAT MATTERS
. . Is simply that through the Monte Carlo (MC) simulative procedure we are able to attain Model Rigorous Sample Statistics (SS) and therefore Testing Hypotheses in a rigorous way.
From the SS we can obtain the respective Cumulative Probabilities (with a controlled maximum error provided by the Dvorestky - Kiefer – Wolfovitz) inequality, then the Critical Values at the conventional Significance Levels).
(Throughout DKW inequality I proved that the fundamental Lilliefors paper (On the Kolmogorov- Smirnov Test for Normality with Mean and Variance Unknown) the Critical Values are correct at 2 decimal places, at most).
The Readers have noted yet the Hypotheses Tests that matters (those without supposed known exact parameters) are WRONG because SS are only more or less approximated.
I don’t know why Jack Tomsky, John Smith (and others) are fighting MC. It’s clear crystal that the cited (gentlemen) has an alibi (?????????):
*** They never read the worlds known Conover’s Practical Nonparametric Statistics where one can find how to get Cumulative Frequencies (Probabilities),
*** They seemly ignored the APPROXIMATIVE character the current Sample Statistics,
*** They admit never met the DKW inequality
HOWEVER
THEY CLAIM TO BE THE EXCLUSIVE Sci Sta Math REFEREES !!!!!!!!.
Absolutely ridiculous isn’t it?
****
Luis Amaral Afonso
(Author of a Monte Carlo paper issued in a referee’s controlled journal Revue de Statistique Appliquee, RSA).
John Smith
When a Monte Carlo created distribution is created, are the 1% and 99% percentiles statistics or parameters?
Bonus question: what is the role of the parameter in a Monte Carlo?
John
Luis A. Afonso
Author: John Smith
Subject: Re: The only thing THAT MATTERS
Nobody should believe anything Afonso writes until he answers these simple questions. When a Monte Carlo created distribution is created, are the 1% and 99% percentiles statistics or parameters? Bonus question: what is the role of the parameter in a Monte Carlo? John ****
MY RESPONSE
Who believes in such a person that is not an author of a paper concerning Monte Carlo Method?
Who believes someone that did not learn that don’t know that the Box-Muller transformation is a rigorous way to get normal values?
How credible is a person that ignores the Conovers Textbook Practical Nonparametric Statistics where one learns how to obtain the Cumulative Frequencies from data?
What to say from a so-called statistician that never met the 1956 Dvorestky- Kiefer- Wolfovitz inequality that teach us how a Empirical Distribution Function is close to the Theoretical one?
How can we trust a person that is ZERO AWARE from thousands papers where Monte Carlo has been used to confirm or deny approach results the Theory provide?
What to say from a person that ask inappropriate questions about a simple DISTANCE (which is the realm of the Lilliefors-Kolmogorov-Smirnov test on normality’
When the samples are created,
In a Monte Carlo Simulation,
One gets the first step merely,
A preliminary point, a situation
To have the Test Distribution.
This one is then constructed
In a way we want, no exception,
It’s elementary, do you see?
Only imbeciles find confusion,
No trouble for true statistician.
Lilliefors test, not excluded
From this clear classification,
Test is only a DISTANCE simply
Any sample how far measuring
The model: what other thing?
The Distance by two guys founded:
Kolmogorov-Smirnov celebration.
Who are able, really, to fight me?
Nobody except an idiot boring
Full addicted in talk rambling.
His litany has any real reaching:
Statistics or Parameters is asking
Not at all, neither, exclusively,
A DISTANCE, not more, clearly.
Who believes some Smith boys,
So much ignorant in this matter
Never Monte Carlo got annoys?
How much Empirical, how better,
Can approach Distribution Function
Should, sure, DKW have instruction!
Such a thing he yet met never.
I’ve not time to spend, surely,
View so great, asinine, opacity.
******
Luis Amaral Afonso
John Smith
John
Luis A. Afonso
Are you saying, IGNORANT JACK, that the Test Statistics of the Lilliefors (Kolmogorov - Smirnov) Test of Normality IS NOT A DISTANCE and trough Monte Carlo one are not able to get he Critical Values?
What paper are you authoring in this area (in a decent Journal) say to us, the Readers?
Don’t you feel ridiculous?
***
Luis Amaral Afonso