Stpasha

Too much TeX

I think you're using TeX too much in this edit. I would much prefer to see x_i rather than $x_{i}\,$. "Diplayed", as opposed to "inline", TeX looks good on Wikipedia. With "inline" TeX the characters often look three or four times as big as the surrounding characters, the TeX is often conspicuously higher or lower than the surrounding text, and periods or commas or the like get badly misaligned or even shifted to the next line.

See spot run

. Spot runs fast.

The period after the first sentence above should be on the same line as the word "run", not the next line. Michael Hardy (talk) 01:22, 2 July 2009 (UTC)

I totally agree that TEX should not be abused in inline formulas, although 3-4 times seems to me like an overexaggeration, it is closer to 1.5 times in my browser. Might depend on browser settings though... do you have text size set to "normal" in your browser? some old browsers (like IE) scale down text size without scaling down picture sizes, which could probably generate your 3-4 times difference.

However in my defense i'd like to point out that not every <math></math> tag gets interpolated into a picture. Simple formulas get converted into HTML markup: compare for example ''x_i'' (which produces x_i) versus <math>x_i</math> (which produces $x_{i}$). Second example is both more readable when editing the article, and is closer to true TEX output since it's using serif fonts.

In the "explanation of notation" section i deliberately forced formulas to render as pictures, with the idea that when they look larger they are more like captions to each bullet point. Well maybe this idea wasn't too sound, but seemed ok to me when i made the edit. // Stpasha (talk) 05:03, 2 July 2009 (UTC)

SmackBot is killing my HTML :(

SmackBot converts following wiki code

<ul>
<li> item 1
     <p> blah-blah-blah
<li> item 2
</ul>

into

<ul>
<li> item 1

blah-blah-blah


<li> item 2
</ul>

Which renders differently in a browser:

• item 1

  blah-blah-blah

• item 2

versus

• item 1 blah-blah-blah
• item 2

// Stpasha (talk) 19:14, 2 July 2009 (UTC)

Hm, tricky.

You could look at using

* item 1 <br> blah-blah-blah
* item 2

• item 1
  blah-blah-blah
• item 2

or

* item 1 
:blah-blah-blah
* item 2

• item 1

blah-blah-blah

• item 2

Rich Farmbrough, 07:08, 3 July 2009 (UTC).

Words and mathematics

Regarding your recent comment in the article on bias, I can think of three reasons for combining English and mathematics. First, writing English sentences helps explain the meaning of the mathematics, and beginning mathematical writers often write mathematical formula and arguments whose shortcomings would become apparent upon being spoken aloud. Second, the formula serves as a mnemonic, so is useful as an addition to the English. Third, some visually impaired Wikipedia-readers may be able to use the written text but not the symbols. It may be that in general wordiness can be removed; it may be that your edits are correct, but I just thought I'd say a word for the loyal opposition. Best regards, Kiefer.Wolfowitz (talk) 12:48, 7 July 2009 (UTC)

Hehe, I welcome opposition :) But will vigorously defend myself! I do think that there are certain places where some spelling/pronounciation hints ought to be added. For example when formula might contain one of the rarer greek letters (ξ, ζ, υ, etc), or even hebrew (eg, $\aleph _{0}$ is commonly used to denote the power of countable sets, but many people will be puzzled how to read this cartoon of a letter). In other cases words will not help and even distract from understanding the formula. Compare “$x^{2}+5x-6=0$” and “an unbeknownst quantity being multiplied with itself and then taken together with the same quantity fivefold would yield six”. As for visually impaired people, the lead sentence of the article already states the definition using words only so they should be ok. // Stpasha (talk) 23:28, 7 July 2009 (UTC)

thanks

didn't realize. just copied and pasted it from the Lvivske article. fixed both now.--Львівське (talk) 19:04, 21 July 2009 (UTC)

Curly quotes

Howdy. At the MOS thread, you mentioned that the "Wikimedia foundation is unwilling to support Q html tags". I was wondering if you'd happen to have a handy link to wherein this is mentioned/alluded to/discussed? Much thanks. :) -- Quiddity (talk) 19:35, 23 July 2009 (UTC)

Hi Stpasha. If you haven't already noticed it, as you requested back in July: I have fixed so the curly quotation marks are grouped and locked together in the edittools. See MediaWiki talk:Edittools#Quotation marks. If you don't see it in the edit window, then you need to bypass your browser cache. (Some web browsers cache the Wikipedia javascripts for up to one month.)

--David Göthberg (talk) 22:50, 22 November 2009 (UTC)

Thanks! Although by now I already figured how to type them on a keyboard (see [1]), this is still a change in the right direction.  … stpasha »  23:32, 22 November 2009 (UTC)

MSE

Hi; thanks for your enhancements to the article. I've changed some of the greek letters back to TeX b/c it looks much cleaner than HTML and is just as compact. Secondly, I have a copy of Cheng & Amin 1982 as a PDF which I bought. The article is also on JSTOR http://www.jstor.org/pss/2345411. I know JSTOR allows those with access to retreive copies freely on a limited basis, so there should be no problem for me to e-mail you a copy of the pdf if you wish. -- Avi (talk) 02:08, 2 August 2009 (UTC)

And as an aside, I for one have no trouble reading Hebrew . -- Avi (talk) 02:09, 2 August 2009 (UTC)

Hehe, I learned how to read א and ב, and luckily no other Hebrew letters are currently used in mathematics — otherwise that would have been a disaster! :) I also was harboring vengeful ideas to use Ж, Ю, or Ъ as mathematical symbols in an article, but then I’d have to come up with an article first…

I for once used to like TeX more too, but then I noticed that it incorrectly renders certain letters in upright font instead of italics, sometimes inserts too many spaces, not to mention that certain simple TeX fails to render as simple HTML and gets converted into images which are larger than surrounding text …

“true” TeX	inline HTML	inline TeX	Scriptstyle TeX
$\theta \,$	θ	$\theta$	$\color {Blue}\scriptstyle \theta$
$n\,$	n	$n$	$\color {Blue}\scriptstyle n$
$(n+1)^{-1}\,$	(n + 1)−1	$(n+1)^{-1}$	$\color {Blue}\scriptstyle (n+1)^{-1}$
$\theta \in \Theta \,$	θ ∈ Θ	$\theta \in \Theta$	$\color {Blue}\scriptstyle \theta \in \Theta$
$\sigma _{\varepsilon }^{2}\,$	σε2	$\sigma _{\varepsilon }^{2}$	$\color {Blue}\scriptstyle \sigma _{\varepsilon }^{2}$
${\tfrac {1}{2}}\,$	½ or 1⁄2	${\tfrac {1}{2}}\,$	$\color {Blue}\scriptstyle {\frac {1}{2}}\,$

... stpasha » talk » 05:53, 2 August 2009 (UTC)

Hi, Stpasha. There is another option for TeX, using \scriptstyle. I've added it to your table above in blue, for comparison. -- Avi (talk) 15:19, 2 August 2009 (UTC)

Hm, nice find. I already forgot about it, as \scriptsyle’s use is to generate font in the size of the subscript. Now regarding that paper you linked — I downloaded a copy myself from jstor — when discussing consistency it first says that consistency was proved in Cheng & Amin (1979), which is a technical report at Cardiff university (I’m not even sure the report exists anywhere except at that university), and then they say that in Cheng & Amin (1982) (another technical report at Cardiff) consistency was proven for 3 particular distributions: Weibull, Gamma and lognormal. So basically they cite unaccessible papers. ... stpasha » talk » 17:12, 2 August 2009 (UTC)

True, the best we can do, I believe, is what I did: cite the accessible paper. The article makes no more claim than does the cited Cheng&Amin paper; beyond that, perhaps we can e-mail Dr. Cheng directly for a copy of those papers. I did e-mail him a number of months ago when starting the article. Oh, and I am completely jealous that you have JSTOR access :) Have you thought about adding yourself to Category:Wikipedians who have access to JSTOR so paupers like me can bombard you with requests :D ?-- Avi (talk) 17:47, 2 August 2009 (UTC)

Regarding the notation, x₍₀₎ = −∞ and x_(n+1) = +∞ is used in Anatolyev+Kosenok’s article in disguise (that article can be downloaded freely from the authors’ website), and also by Ekström in the (2001) “Consistency of generalized maximum spacing estimates” (I can send you the pdf if you tell me your address; my gmail address is the same as my wikipedia’s username). That article also proves the consistency for the generalized MSE, we only need to figure out which of those conditions are superficial in the “regular” MSE case.

I also wonder if there is a point in replacing simple ''θ'' with <math alt="theta">\theta</math>, and also what those “alt” attributes do (I thought the engine already generates alt text for images with the TeX code of the content). ... stpasha » talk » 23:30, 2 August 2009 (UTC)

Re: Ekstrom, e-mail on the way. Re: "alt", I am not sure, and there is a line on WP:ALT about adding manual alt notes, although that is impossible for display mode. If that is not necessary, I'd be glad to get rid of the alt text. -- Avi (talk) 23:36, 2 August 2009 (UTC)

Stpasha, I came here for another reason but was interested in this thread. I would support the view that inline HTML is preferable to inline TeX where the use of inline HTML doesn't detract from the content meaning. Three reasons:

• Each occurrence of inline TeX generates an image tag that needs to be downloaded and rendered, e.g. <img class="tex" alt="(n+1)^{-1}\," src="http://upload.wikimedia.org/math/3/5/9/3594f31691e6c6f1e23a4806968cc56a.png" /> which incurs additional HTTP overheads effecting both rendering times aliasing issues when scaling.
• The inline HTML is rendered by the browser using true scalable fonts and the result is a lot more pleasing to the reader. Ease of reading is important.
• There is an additional server-side burden.

I also like the <sup style="position:relative;left:-.4em"> trick, BTW. Nice one. Thanks for pointing it out. -- TerryE (talk) 10:52, 14 May 2010 (UTC)

Inkscape

Well, I guess I can console myself that I just started using it last week, what you did was fantastic. There is so much one can learn, and so little time to learn it. Do you have any suggestions for quick primers? Thank you again! -- Avi (talk) 22:45, 3 August 2009 (UTC)

Well, that’s my second picture in Inkscape, first one for the Ordinary least squares article (“geometry of OLS”). So I already learned that it’s best to vectorize all text labels (“Object to Path” function). An alternative would probably be to embed the definition of all glyphs used into the image, but I haven’t figured out how to do that… ... stpasha » talk » 06:52, 4 August 2009 (UTC)

Slutsky's theorem

Can you please add a citation or a justification for your statement "This theorem follows from the continuous mapping theorem and the portmanteau theorem"? In Grimmett & Stirzaker it is really just an exercise without a solution, and the proofs I saw in the literature are a bit more complicated than that. Please see this edit which points out that it does not follow immediately from the continuous mapping theorem (which I wrote in the article earlier myself). Also, there is Slutsky's theorem in n-dimensions, but I did not see it anywhere in infinite dimension while the continuous mapping theorem and the portmanteau theorem do hold in infinite dimension. Thanks! Jmath666 (talk) 15:48, 13 September 2009 (UTC)

I was going to add the proof to the theorem yesterday, but fell asleep :) Now it’s there. The proof becomes quite simple once we establish the fact that (X_n, Y_n) converges in distribution to (X, c) — the fact which can be shown using the portmanteau lemma. As for the infinite dimensions, I believe it does hold in that generality, only most textbooks never consider infinitely-dimensional random variables, so there is no need for them to overexert themselves. ... stpasha » talk » 19:48, 13 September 2009 (UTC)

Thanks! If you know of reference that shows that (X_n, Y_n) converges in distribution to (X, c) in infinite dimension that would be nice. Jmath666 (talk) 22:25, 13 September 2009 (UTC)

I added the proof to the Convergence of random variables/Proofs#propB3 page; and it doesn’t seem it uses any finite-dimensional assumptions. Hope the article won’t get deleted by the time you get there :) ... stpasha » talk » 05:48, 14 September 2009 (UTC)

mos for images

at normal distribution, you mention a MOS for images. Where is this? PDBailey (talk) 17:14, 23 September 2009 (UTC)

I’m not aware of a specific MoS for images, but as far as the image contains text labels, those text labels are governed by the usual WP:MOS and the conventions for displaying math formulas. There is also the tutorial WP:HCGWA, but they never emphasize the point that if the graph is to be displayed in thumbnail, it should be scaled down properly, so that all lines and labels are still legible. Some of the examples on that tutorial page show exactly the opposite situation.

As an example take a look at pictures in the “Convergence of random variables” article: the first one (convergence in distribution) is clear and legible, while the second (section convergence in probability) is quite to the contrary barely visible and the text labels can't be seen at all (well that’s not even to mention that the picture in fact demonstrates convergence almost surely, but that’s already details)  … stpasha »  17:57, 23 September 2009 (UTC)

Initial context-setting

Please look at this edit. I don't think "measure theory", by itself, tells the lay reader that mathematics is what it's about. "Number theory" or "algebra" or "geometry" or "calculus" suffices, but "measure theory" is something most lay readers have never heard of. Michael Hardy (talk) 00:38, 7 December 2009 (UTC)

Never confused?

If we leave only one definition (leaving the other one as a short subsection describing the differences in the alternative formulation), it has following advantages: (1) the reader will never get confused regarding which definition is used on the page,

I'm amazed that you say the reader will never get confused. We had years of experience with this in geometric distribution. The article was full of emphatic notices that there were two different definitions, and we still had idiots coming along incessantly citing a textbook that gave a different mean or mfg from the one the article gave and expressing shock that such an error would be there, and then "correcting" it. Only putting BOTH columns there put an end to (most of) that. That's what happened when readers never got confused. Michael Hardy (talk) 22:00, 12 December 2009 (UTC)

Ok, maybe “never confused” is an overstatement, yet I stand by my initial suggestion. Of course, the two-column infobox might be fixing the problem with overzealous idiots, however it also introduces some new problems, which may not be immediately obvious:

• The infobox doesn't explain why there are two columns in it, and what do they mean. Of course it is mentioned in the lead of the article, however as a rule an infobox must be self-sufficient and not rely on the surrounding text to put it into context.
• The two-column infobox is confusing to the new readers who come to the page without preliminary knowledge of what the geometric (or negative binomial) distribution is.
• The infobox is too wide, on low-resolution monitors (or in browsers which are not opened in fullscreen) this infobox breaks the page layout, making it difficult to read. As a general rule, the page should be readable on 1024px width monitor.
• There is no clear indication in the subsequent text on the page regarding which of two definitions provided is used. For example, the very first section says “the expected value of a geometric distribution is 1/p”... Of course all such issues can be carefully fixed, however it'll either unnecessarily bloat the amount of text on the page, or will leave the reader with impression that not all cases were actually covered.
• The template for 2-column infobox is not derived from the single-column template. As such, any changes introduced into the single-column template will not be applied to the 2-column template, which will gradually lead to style inconsistencies (well, actually it already have lead).

Now it seems to me that an alternative solution can be used to deter the self-confident editors: use a standard 1-column infobox, but put a nice noticeable warning in bold font right at the top of the infobox; a warning about the 2 (or more) alternative definitions.  … stpasha »  08:56, 13 December 2009 (UTC)

Revert comment

I changed Ordinary least squares/Proofs to a redirect as part of an effort to clean up math articles with titles that do not conform to Wikipedia naming conventions. See the talk page for that article for more information. I apologize if I was hasty in my evaluation of the content of the article, However, I don't appreciate my change being marked as vandalism when it wasn't. In the future, please WP:Assume good faith.--RDBury (talk) 15:37, 16 January 2010 (UTC)

I'm sorry for misunderstanding your intentions; however it is my point of view that the contents of the article should be kept, and I gave my reasons at the article’s talk page.  … stpasha »  17:56, 16 January 2010 (UTC)

Negative binomial distribution

You said:

Please, before reverting the edit and asserting that I “completely ignored the discussion on the talk page”, make sure you have read that discussion. There was a 1-month old proposal (section Major Changes) to simplify the exposition down to only 1 main definition, and that proposal was met with a (cautious) support.

The main reason why we had 2-column infobox is because readers were frequently confused when they seen apparent discrepancies between the article and their textbooks. Such confusion can be avoided either by bloating the infobox (and actually there are more than 2 possible definitions), or by including a very noticeable alertbox, warning about potential discrepancies when comparing this info to existing textbooks, which is the way we are dealing with the problem right now. … stpasha » 18:55, 19 January 2010 (UTC)

WP:EP says:

Be cautious with major changes: consider discussing them first. With large proposed deletions or replacements, it may be best to suggest changes in a discussion, to prevent edit warring and disillusioning either other editors or yourself (if your hard work is rejected by others). One person's improvement is another's desecration, and nobody likes to see their work "destroyed" without prior notice. If you choose to be very bold, take extra care to justify your changes in detail on the article talk page. This will make it less likely that editors will end up reverting the article back and forth between their preferred versions.

Whatever discussion there was was not explicitly about the types of changes you have made, which should have been proposed in detail. Melcombe (talk) 10:21, 20 January 2010 (UTC)

Sigma algebra too technical?

Hi Stpasha, please see talk:Sigma-algebra#Too technical?, thanks. Paul August ☎ 15:18, 20 January 2010 (UTC)

law of the unconscious statistician

Looks like I was unconscious when I added it. It was in the wrong place. it is that if Y = g(x) then E(Y) = E(g(x)) = int(g(x)f(x)dx) where f(x) is the pdf. 0¹⁸ (talk) 19:00, 20 January 2010 (UTC)

Your Proof is wrong !!!

In the consistency of maximum likelihood, you put

$\operatorname {E} [-\ln(a)]=\operatorname {E} {\big [}\ln f(x_{i}|\theta _{0})-\ln f(x_{i}|\theta ){\big ]}=\ell (\theta _{0})-\ell (\theta )$

should be

$\operatorname {E} [-\ln(a)]=\operatorname {E} {\big [}\ln f(x_{i}|\theta _{0})-\ln f(x_{i}|\theta ){\big ]}=E\ell (\theta _{0})-E\ell (\theta )$

which dose not support your conclusion !!!

I knew the 4 conditions is more general in supporting the conclusion, but i don't think it intuitive enough for people to understand the proof.

I think my previous is making more sense. —Preceding unsigned comment added by Xappppp (talk • contribs) 06:52, 25 January 2010 (UTC)

The proof is correct. We denote

${\hat {\ell }}(\theta )={\frac {1}{n}}\sum _{i=1}^{n}\ln f(x_{i}|\theta )\equiv {\widehat {\operatorname {E} }}{\big [}\ln f(x_{i}|\theta ){\big ]}$

and its probability limit when n → ∞ as

$\ell (\theta )=\operatorname {E} {\big [}\ln f(x_{i}|\theta ){\big ]}.$

 … stpasha »  07:46, 25 January 2010 (UTC)

Under your notation, still the consistency is not clear in your proof. Xappppp (talk) 15:17, 25 January 2010 (UTC)

Because this is not the proof of consistency, only its most crucial part. The proof given in "Consistency" section establishes a remarkable fact that if the model is identified, then the likelihood function will have a unique maximum. From that point on, the consistency follows from the general theory for extremum estimators.  … stpasha »  06:54, 26 January 2010 (UTC)

MLE and Bayes: Le Cam and Ferguson

Dear Stpasha,

You reversed an edit of mine, saying that Bayes estimators had better asymptotic properties than mle, with the statement that my sources did NOT support that statement. This statement was unfortunate because Le Cam and Ferguson do support that statement, as I'll document.

My text referred to Le Cam---not Le Cam and Yang. Le Cam's 1986 book discusses Bayesian estimators e.g. in Chapter 17.7 and then goes from wine to dish-water with mle, showing that (no "the" btw) "mle is not that trustworthy" (page 623). These examples can also be found in the ISI article I listed, which is available in JSTOR.

I believe that you are referring to the second edition of Le Cam & Yang, which has an example of bad behavior of Bayes, however using the axiom of choice's implication that the real line is the union of a set of measure zero and another set meager in the Baire categoric sense. (This would be relevant to the discussion if the mle had better behavior, and I would be very surprised if Le Cam had any statement like that!)

I believe Le Cam comments that the log-normal distribution wasn't a mathematical demon conjured to bedevil Ronald Fisher!

Chapter 21 of Ferguson discusses the asymptotic normality of posterior distributions, and the Bernstein von-Mises Theorem shows "something slightly stronger", about convergence of densities. Exercise 2 in that chapter is the uniform distribution on the open interval, where no mle exists, but Bayes has no trouble, but he doesn't spell out this triviality. Ferguson does state that the mle is asymptotically equivalen to Bayes, when both exists. Ferguson gives examples where mle doesn't. Ferguson's treatment of the mle follows Cramér --- if you insist on "maximum" likelihood estimation, you can only prove weaker results.

Kiefer.Wolfowitz (talk) 21:24, 26 January 2010 (UTC)

I'm sorry for this misunderstanding from my part. The reference said “Le Cam”, and I immediately assumed that it refers to that Le Cam’s book that I have >.<

Now regarding the "MLE is not that trustworthy" comment of Le Cam. (Haven't had read it myself), I bet what he really means is that MLE is not really a panacea for every occasion. For example, the consistency theorem contains 1 substantial and 3 technical conditions, and one give examples of models where those conditions are violated, rendering MLE inapplicable. And of course the estimators for those models can still be constructed (they can even be the Bayes estimates).

However I don't think there is a single method which works in every single case. And I don't think that Bayesian methods are "superior" to MLE, meaning that they work within a strictly weaker set of assumptions. For once, they require additional knowledge of the prior, and the properties of Bayesian estimator will depend upon whether the prior was good or not…

In any case, the possible comparison of MLE with other methods can be done in its own section, but probably shouldn't be interspersed in the main text.  … stpasha »  07:40, 27 January 2010 (UTC)

Dear Stpasha:

Thank you for your understanding. However, you are mis-informed about Bayesian estimators (at least in terms of their asymptotic properties for finite-dimensional problems, which were the only place I discussed them). The Bernstein-von Mises (Laplace) theorem concludes that the posterior asymptotics are independent of the prior (that is positive on the parameter space, obviously).

(This is why Laplace was able to reduce asymptotics to the Fisher (sic.) information!)

I forget the Freedman-Diaconis example sketched in Le Cam and Yang, but I believe it is infinite dimensional.

LeCam proved a theorem that it suffices to start with any consistent estimator and take one Newton step to recover the (first-order) asymptotics of mle (Ferguson). Such results falsify the article's uniqueness claims, which are widely believed, despite 50 years of counter-examples.

A remaining problem is to check whether the article's asymptotic results are proved for only consistent sequences of zeros of the score function, although the results seem to be stated for only maxima (certainly in the introduction).

Best regards, Kiefer.Wolfowitz (talk) 12:27, 27 January 2010 (UTC)

"Articles that suffered from my attention"

Thanks for your (self-deprecating) humor (on your USER page), and of course your editing! Kiefer.Wolfowitz (talk) 23:53, 7 March 2010 (UTC)

Ty, it’s all good fun :)  // stpasha »  23:59, 7 March 2010 (UTC)

Codomain of a random variable: observation space?

Your opinion is welcome at Wikipedia talk:WikiProject Mathematics#Codomain of a random variable: observation space?. Boris Tsirelson (talk) 16:42, 27 March 2010 (UTC)

move to "linear regression model"?

What are the reasons for this edit? All other things being equal, a shorter name is better. People are far less likely to link to "linear regression model" than to "linear regression". Michael Hardy (talk) 17:17, 21 April 2010 (UTC)

Actually that's not true, there were at least several articles linking to [[Linear regression]] [[statistical model|model]]. The reason behind this move is that we already have General linear model, Generalized linear model, Errors-in-variables models, Probit model, Logit model, and other types of regression models (we also have Discrete choice which does not adhere to the pattern, however I believe it should be renamed as well). The name “Linear regression” is ambiguous — it could correspond to either a statistical linear model (alas we have that as an article too), or to the process of estimation, which is commonly taken as a synonym for OLS — simple linear regression is an example of such confusion. Even if people are more likely to link to “Linear regression” it is probably because they are likely to get confused what does that mean. My vote is to move the article back to the “Linear regression model” and perhaps convert “Linear regression” into a disambig page.

I suggested the move quite some time ago, and there was a weak support for it.  // stpasha »  17:45, 21 April 2010 (UTC)

I think you should start a new section at talk:linear regression and state your case not quite as hastily as you do in the paragraph above. And also link to it from Wikipedia talk:WikiProject Statistics. Michael Hardy (talk) 20:20, 21 April 2010 (UTC)

Apostrophes

The preferred apostrophe on Wikipedia is the usual "straight" one; see WP:PUNC. — Carl (CBM · talk) 15:39, 5 May 2010 (UTC)

I have seen it. Unfortunately, this is the part where WP:MOS is not reliable. If you look into the Talk: archives you will see that there was a heated ongoing discussion regarding this issue, and there was a consensus that the current standard has to be changed. The only problem is that MOS is protected from editing. The preferred glyph for apostrophe is ’, as opposed to prime ′ or straight vertical glyph ' (which doesn’t even have a proper name since it doesn’t have a proper usage).  // stpasha » 

Could you link me to that talk page? I had seen some discussion on it, but I didn't follow it closely, and I thought the agreement was to keep the straight quotes. — Carl (CBM · talk) 16:58, 5 May 2010 (UTC)

Here it is, at least that’s the discussion I’ve participated in. There could have been more debates in the subsequent archives.  // stpasha » 

Thanks. I try to stay out of those discussions, so I don't really know what the overall trend is. I was relying on the MOS itself to be somewhat accurate, although I know that isn't always the case. — Carl (CBM · talk) 01:40, 6 May 2010 (UTC)

How could you do such things?

Consensus was there for the move as I read the discussion at the end. One of the points raised that was not refuted is that if there is no need for a dab page, then why should the article not be at the main name space adding a hat note as needed. Also if you looked at the inbound links, exclusive of the templates, they were mainly for linear regression which supported the decision. I'll also add that a disambiguation page is not always needed. When there are only two terms that could be considered, then a hat note is considered sufficient. If you decide to renominate, please allow the editors some time to get the archives sorted out since the previous moves appeared to not have moved the archives with the articles. This is an issue at either name. Also checking on Google you notice that it does not even suggest 'linear regression model' after entering "linear regression" and there is a significant difference in the number of hits. "linear regression" gets 3,340,000 hits and "linear regression model" gets 329,000 hits. So the case is there for what the common name is. Vegaswikian (talk) 23:13, 11 June 2010 (UTC)

1. I don’t know whether a dab page is needed or not, but it certainly seems that too often people link to linear regression when in fact they meant to link to ordinary least squares. Which means people are getting confused, which means they have to be disambiguated. Also as people have pointed out, there should be more than just 2 items on that dab page, in particular it should include link to the simple linear regression, and probably to the general linear model as well.

2. When I look at the inbound links, hiding redirects and restricting attention only to (Article) namespace, i get 186 links to “linear regression” and 259 links to “linear regression model”. Some of the links in the former category should have been in the latter: for example, see linear model article which says “… the term is often taken as synonymous with linear regression model.” Some other articles that link to linear regression in fact meant to link to OLS (say — I took at random — the Francis Anscombe article, which talks about Anscombe’s work about the residuals from least squares regression, not just any linear regression). Of course, some of the links in the latter category might be piped, so they aren’t a perfect indicator either.

3. I agree that judging by the Google counter “linear regression” is a very common name. The question is: what exactly is it common for? Turns out, it’s a name common for the ordinary least squares, or for the simple linear regression (which should be properly named “simple least squares”, or something like that). However the article we are talking about is an outline-type article about different approaches for estimating the linear regression fit. Which is why I find it most appropriate for it to have this long and somewhat awkward name.

 // stpasha »  01:02, 12 June 2010 (UTC)

I have marked you as a reviewer

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pdf

I doubt you'll be surprised to learn I agree. Cheers, Pdfpdf (talk) 14:19, 7 July 2010 (UTC)

GA status for normal

Sure, I would be willing to help. I'm pretty good at writing, and can definitely help improve the writing quality of the article. I'm not so familiar with the references that we would need to quote, so you might have to take the lead on that. Benwing (talk) 02:07, 12 October 2010 (UTC)

Komlós–Major–Tusnády approximation

I noticed your edits on the empirical distribution function. Just giving you a heads up on a new stub on hungarian embedding. Also why did you remove reference to the Berry–Esseen theorem there? I thought it was relevant. (Igny (talk) 02:24, 14 October 2010 (UTC))

I'm pretty sure I haven't removed that reference. At least looking through the history it doesn't seem to ever been there... On the other hand I can't see why Berry–Esseen theorem is relevant to the empirical distribution function article. Oh and good job on the Hungarian embedding!  // stpasha »  06:26, 14 October 2010 (UTC)

License tagging for File:Nes logo en.gif

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AWB

Hi there Stpasha. Just letting you know I've removed your account from the AWB list of bots (you were apparently mistakenly added here). I've added you to the users list instead, so you will still have access to AWB's non-bot functions. Cheers, - Kingpin¹³ (talk) 13:52, 2 November 2010 (UTC)

ƒ

Hi, Stpasha. I noticed you recently reverted an edit of mine in which I replaced the symbol ƒ in a mathematics article with the letter f; your explanation was that "the use of symbol ƒ to denote function is recommended by math styleguide." I am curious where you are reading this. I looked through MOS:MATH and didn't see anything. I see that ƒ is listed at Wikipedia:Mathematical symbols as a symbol available in HTML that should work in most browsers, but that is not a recommendation for its use. —Bkell (talk) 16:33, 10 November 2010 (UTC)

Hmm, I haven't received any response from you, so I'm going to replace ƒ with f again. It seems to me that since there is no special symbol for a function named g or h, it doesn't make sense to use some special symbol for a function named f. The symbol used in mathematical papers isn't a Latin small letter F with hook—it's just an italic f. —Bkell (talk) 11:50, 18 November 2010 (UTC)

The symbol used in mathematical papers is $f$, which renders as $f\,$. Note that the default <math/> renderer also uses the symbol with a hook: $f$. I don't know where this came from, and whether or not we have a styleguide to recommend it, but my guess is that it improves readability, similarly how ℓ is better than l in math mode. I'd also like to point out that the symbol ƒ in HTML is the entity &fnof;, which is “function of”, so it is in fact intended to be used as a function name.  // stpasha »  16:12, 18 November 2010 (UTC)

No, the default math renderer does not produce the symbol ƒ—it produces the letter f in an italic serif font. (Copy the symbol into the Wikipedia search box if you don't believe me; the HTML produced is <span class="texhtml"><i>f</i></span>.) The symbol ƒ looks similar, but is not the same: ƒ. —Bkell (talk) 17:30, 18 November 2010 (UTC)

I've replied over at Wikipedia talk:WikiProject Statistics#ƒ or f. —Bkell (talk) 17:41, 18 November 2010 (UTC)

Normal distribution erf table

I added several rows to the lower table to roughly match the same number of sigma multiples, i.e., 6, as in the upper table. I did not intend for it to continue growing. Currently the lower table does not go as far (~4 sigma) as the upper one (~6 sigma).59.115.245.74 (talk) 12:15, 15 November 2010 (UTC)

Well, the problem is that the second table already has more rows than the first one, and adding extra ones only exaggerates the problem. Perhaps the compromise solution would be to make the second table in 4 columns (like a multi-column list).  // stpasha »  05:51, 16 November 2010 (UTC)

Okay, followed your suggestion, see if it looks okay. Thanks.140.96.158.67 (talk) 05:09, 19 November 2010 (UTC)

Great, looks much better after your edit. Couldn't get the precision with Excel.218.35.228.21 (talk) 18:36, 20 November 2010 (UTC)

surd symbol

Just a quick comment about the latex \surd symbol used for the skewness coefficient. The \surd symbol is used in the skewness literature rather than the square root; it is not a typesetting misfortune. If square root would be used, then typically it indicates the positive root unless a sign is there. Skewness is a signed coefficient. So the use of the \surd is actually correct in this context, though it may look odd. Mathstat (talk) 02:32, 2 February 2011 (UTC)

Probability distribution merge

In October you made this and related edits [2]. I cannot see any discussion so I have removed the tags. --Rumping (talk) 18:18, 2 February 2011 (UTC)

Overrating your Engllish skills.

In particular, the edits I made remedied a defect, to which you as a native speaker of lang(s) without articles are oblivious. You're too quick to revert other's edits as the above shows. 72.228.177.92 (talk) 22:05, 19 February 2011 (UTC)

If you are referring to this edit of yours, then it was not about the articles. You inserted "(PDF)" as an abbreviation for probability density function, which is completely unnecessary since the article is not about the pdf's, and this abbreviation is more of a slang than standard lingo. Also, the phrase "standard normal PDF" is incorrect, it should be the "standard normal distribution". Now, since there is already one word "distribution" in the sentence, the second encounter may be omitted according to standard rules of English.

As for my skills with articles a/the, I'm not very proud of them --- so if you see my mistake somewhere, you're welcome to correct it. // stpasha » 07:42, 20 February 2011 (UTC)

This was a very gentle, helpful, and kind reply to a comment that needed to be more gentle, helpful, and kind.  Kiefer.Wolfowitz  (Discussion) 14:50, 20 February 2011 (UTC)

It does not matter that the article is not "about" PDFs, they are central to the particular thing which it is about, and before my edit the acronym was used (in the infobox) without explanation, albeit as a link. I have had personal experience of the ignorance of the average citizen on what a PDF is and therefore am especially sensitive. Kiefer: the comment was helpful, this individual is showing an arbitrary attitude of ownership that is in violation of a number of wiki policies, and I'm not the first to comment on it on this page. My communications have been civil, and in fact helpful. The other properties are without function, especially in response to their opposite. In a matter common to wiki articles there is a misidentification/mismatch of the subject matter to the title which is either an aggravation or justification for the editors action/attitude. SFAICT the actual title should be The Normal Curve, oder, as there are several distinct things which are different aspects of the one encompassing definite article. 72.228.177.92 (talk) 23:52, 20 February 2011 (UTC)

I undid your edit not because of my "ownership of the article", but because I found it partly unhelpful partly incorrect. Unhelpful, because it could be helpful to explain an abbreviation: "pdf (probability density function)", but there is no point in complicating things by abbreviating an already spelled-out term: "probability density function (pdf)". The second part was incorrect, because the article is not about the curve, it is not about the density, it is about the normal distribution. The title accurately reflects the subject.  // stpasha »  02:04, 21 February 2011 (UTC)

Concluding this on a positive note, I am glad that you are writing in English and that a species mired in ignorance and backwardness yet has large numbers of individuals like yourself pushing back the darkness. My edits while defensible I believe, I'm happy to have give way to your zeal in making Normal distribution a better article. 72.228.177.92 (talk) 14:48, 22 February 2011 (UTC)

Please check this edit to Variance

Hi, an IP with no history has changed your edit of 27 October 2009 on the variance of the estimator of the variance -- he has changed $\sigma ^{4}$ to $\sigma ^{2}$. See [3]. Can you check to make sure this is right? Duoduoduo (talk) 19:46, 2 April 2011 (UTC)

log plot

Hi, you once create File:Logarithm_plots.svg which is shown right at the top of logarithm. An FAC reviewer rightfully points out that the labels at the negative y-axis should not be spaced and should use a &minus; (as opposed to a hyphen "-"), i.e., should read "−1" as opposed to "- 1". Is it possible for you to fix this in the illustration? I'm not so much into svg, and I figure it is an easy game for you. Thank you for your help! Jakob.scholbach (talk) 20:18, 26 April 2011 (UTC)

Also, is it possible to remove all the dotted lines and dots, except for the one at (2,1) and adding one at (8,3)? Thank you again! Jakob.scholbach (talk) 20:47, 26 April 2011 (UTC)

The reason I'm asking is that I want to make the image caption more instructive for outsiders and need the image to match this purpose. Jakob.scholbach (talk) 20:48, 26 April 2011 (UTC)

Normal distribution

Hi, I had to brush up my knowledge on the Normal distribution and read the article from top to bottom. I think it is a wonderful article and just wanted to thank you for your hard work (from a quick look at the history you seem to be the main contributor). I especially like the fact that it is comprehensive and approaches the subject from many angles. Keep up the good work, --Voorlandt (talk) 20:39, 6 December 2011 (UTC)

Invitation to comment at Monty Hall problem RfC

You are invited to comment on the following probability-related RfC:

Talk:Monty Hall problem#Conditional or Simple solutions for the Monty Hall problem?

--Guy Macon (talk) 17:14, 8 September 2012 (UTC)

File:Nes logo en.gif missing description details

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MOS Register

Hi, Stpasha!

I was just looking around the Manual of Style Register and came across the section on "Curly or straight" quotes that you expanded in 2010. I noted that you used the {{xt}} and {{!xt}} templates in an unusual way and wondered if you could clarify what you had intended. These templates are usually used to highlight right and wrong examples of style but are not used in this way in this case. Perhaps you just used them to highlight certain text that would be more accurately achieved by the use of bold, italics or highlighting. Could you shed any light on this? Sorry, I realise this is going back some time; I've only just stumbled upon it and it has me scratching my head.

Cheers! —sroc 💬 18:34, 11 January 2015 (UTC)

ArbCom elections are now open!

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ArbCom elections are now open!

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Possible removal of AWB access due to inactivity

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regarding your contribution in an article (you've got mail)

Hello, Stpasha. Please check your email; you've got mail!
It may take a few minutes from the time the email is sent for it to show up in your inbox. You can at any time by removing the {{You've got mail}} or {{ygm}} template.Statstudent5 (talk) 15:52, 22 December 2020 (UTC)

Hi,

I saw you being the author of an excellent contribution: https://en.wikipedia.org/wiki/Unbiased_estimation_of_standard_deviation#Other_distributions

However I am in urgent need of a reference for this formula: https://wikimedia.org/api/rest_v1/media/math/render/svg/7c03af4ff7000635c861b4e28f7cb99958148333

"where γ2 denotes the population excess kurtosis. The excess kurtosis may be either known beforehand for certain distributions, or estimated from the data."

If there is no reference, at least a way of deriving this.

Thank you for your help.

Best

unbiased estimation (continuation)

@Stpasha: please see the message above

"L² norm" listed at Redirects for discussion

An editor has identified a potential problem with the redirect L² norm and has thus listed it for discussion. This discussion will occur at Wikipedia:Redirects for discussion/Log/2022 May 4#L² norm until a consensus is reached, and anyone, including you, is welcome to contribute to the discussion. fgnievinski (talk) 22:03, 4 May 2022 (UTC)