#### [Book] The Elements of Statistical Learning, 2nd Ed.

__This was written more than a year ago, and I forgot to post it.__

Continue reading ‘[Book] The Elements of Statistical Learning, 2nd Ed.’ »

Weaving together Astronomy+Statistics+Computer Science+Engineering+Intrumentation, far beyond the growing borders

Posts tagged ‘book’

__This was written more than a year ago, and I forgot to post it.__

Continue reading ‘[Book] The Elements of Statistical Learning, 2nd Ed.’ »

by **P.I.Good** and **J.W.Hardin**. Publisher’s website

My astronomer neighbor mentioned this book a while ago and quite later I found intriguing quotes. Continue reading ‘Quotes from *Common Errors in Statistics*’ »

A number of practical Bayesian data analysis books are available these days. Here, I’d like to introduce two that were relatively recently published. I like the fact that they are rather technical than theoretical. They have practical examples close to be related with astronomical data. They have R codes so that one can try algorithms on the fly instead of jamming probability theories. Continue reading ‘[Books] Bayesian Computations’ »

**Kriging** is the first thing that one learns from a spatial statistics course. If an astronomer sees its definition and application, almost every astronomer will say, “Oh, I know this! It is like the 2pt correlation function!!” At least this was my first impression when I first met **kriging.**

There are three distinctive subjects in spatial statistics: **geostatistics**, **lattice data analysis**, and **spatial point pattern analysis.** Because of the resemblance between the spatial distribution of observations in coordinates and the notion of spatially random points, spatial statistics in astronomy has leaned more toward the spatial point pattern analysis than the other subjects. In other fields from immunology to forestry to geology whose data are associated spatial coordinates of underlying geometric structures or whose data were sampled from lattices, observations depend on these spatial structures and scientists enjoy various applications from geostatistics and lattice data analysis. Particularly, **kriging** is the fundamental notion in **geostatistics** whose application is found many fields. Continue reading ‘[MADS] Kriging’ »

I was reading Lehmann’s memoir on his friends and colleagues who influence a great deal on establishing his career. I’m happy to know that his meeting Landau, Courant, and Evans led him to be a statistician; otherwise, we, including astronomers, would have had very different textbooks and statistical thinking would have been different. On the other hand, I was surprised to know that he chose statistics over physics due to his experience from Cambridge (UK). I thought becoming a physicist is more preferred than becoming a statistician during the first half of the 20th century. At least I felt that way, probably it’s because more general science books in physics and physics related historic events were well exposed so that I became to think that physicists are more cooler than other type scientists. Continue reading ‘[Book] The Physicists’ »

by **T. Cover and J. Thomas** website: http://www.elementsofinformationtheory.com/

Once, perhaps more, I mentioned this book in my post with the most celebrated paper by Shannon (see the posting). Some additional recommendation of the book has been made to answer offline inquiries. And this book always has been in my favorite book list that I like to use for teaching. So, I’m not shy with recommending this book to astronomers with modern objective perspectives and practicality. Before advancing for more praises, I must say that those admiring words do not imply that I understand every line and problem of the book. Like many fields, Information theory has grown fast since the monumental debut paper by Shannon (1948) like the speed of astronomers observation techniques. Without the contents of this book, most of which came after Shannon (1948), internet, wireless communication, compression, etc could not have been conceived. Since the notion of “**entropy**“, the core of **information theory**, is familiar to astronomers (physicists), the book would be received better among them than statisticians. This book should be read easier to astronomers than statisticians. Continue reading ‘[Book] Elements of Information Theory’ »

A continuation from my posting, titled circumspect frequentist.

Title: **Statistical Models: Theory and Practice** (click for the publisher’s website)

My one line review, rather a comment several months ago was

Bias in asymptotic standard errors is not a familiar topic for astronomers

and I don’t understand why I wrote it but I think I came up this comment owing to my pursuit of modeling measurement errors occurring in astronomical researches. Continue reading ‘A book by David Freedman’ »

The first issue of this year’s IMS bulletin has an obituary, from which the following is quoted. Continue reading ‘Circumspect frequentist’ »

All of a sudden, partially owing to a thought provoking talk about visualization by Felice Frankel at IIC, I recollected a book, The Grammar of Graphics by Leland Wilkinson (2nd Ed. – I partially read the 1st ed. and felt little of use several years ago because there seemed no link for visualization of data from astronomy.) Continue reading ‘[Book] The Grammar of Graphics’ »

Another deduced conclusion from reading preprints listed in arxiv/astro-ph is that astronomers tend to confuse **classification and clustering** and to mix up methodologies. They tend to think any algorithms from classification or clustering analysis serve their purpose since both analysis algorithms, no matter what, look like a **black box**. I mean a black box as in neural network, which is one of classification algorithms. Continue reading ‘Classification and Clustering’ »

Talking about limits in Numerical Recipes in my PyIMSL post, I couldn’t resist checking materials, particularly updates in the new edition of Numerical Recipes by Press, et al. (2007). Continue reading ‘NR, the 3rd edition’ »

I have been observing some sorts of misconception about statistics and statistical nomenclature evolution in astronomy, which I believe, are attributed to the lack of references in the astronomical society. There are some textbooks designed for junior/senior science and engineering students, which are likely unknown to astronomers. Example-wise, these books are not suitable, to my knowledge. Although I never expect astronomers to learn standard graduate (mathematical) statistics textbooks, I do wish astronomers go beyond Numerical Recipes (W. H. Press, S. A. Teukolsky, W. T. Vetterling, & B. P. Flannery) and Error Data Reduction and Analysis for the Physical Sciences (P. R. Bevington & D. K. Robinson). Here are some good ones written by astronomers, engineers, and statisticians: Continue reading ‘Books – a boring title’ »