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Another text in the CRC series Markov Chain Monte Carlo in Practice by Gilks, Richardson and Spiegelhalter provides more detail on these methods along with many applications including some Bayesian ones.
This book's biggest strength is its introduction of most of the important ideas in Bayesian statistics through well-chosen examples. These are examples are not contrived: many of them came up in research by the authors over the past several years. Most examples follow a logical progression that was probably used in the original research: a simple model is fit to data; then areas of model mis-fit are sought, and a revised model is used to address them. This brings up another strength of the book: the discussion and treatment of measures of model fit (and sensitivity of inferences) is lucid and enlightening.
Some readers may wish the computational methods were spelled out more fully: this book will help you choose an appropriate statistical model, and the ways to look for serious violations of it, but it will take a bit of work to convert the ideas into computational algorithms. This is not to say that the computational methods aren't discussed, merely that many of the details are left to the reader. The reader expecting pseudo-code programs will be disappointed.
All in all, I recommend this book for anyone who applies statistical models to data, whether those models are Bayesian or not. I especially recommend it for researchers who are curious about Bayesian methods but do not see the point of them---Chapter 5, and particularly section 5.5 (an example chosen from educational testing), beautifully addresses this issue.
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David emigrated to Canada in 1957 with only $40 in his pocket. Now, after 39 years in the life insurance business, he sells $100 million dollar cases. His new book reveals, for the first time anywhere, the strategies he has used throughout his life to open new markets, prepare for cases and close sales.
Right from page one, Breakthrough: Take Your Business to the Top grips the reader and doesn't let go. It is written in a fast-paced, easy-to-understand style. David Cowper takes the reader deep inside the psychological drama of over thirty different cases that cover all of the different stages of his long career. In each case I felt as if I was right inside the prospect's office with him, straining to overcome the client's objections, feeling heartbroken when the case seemed to collapse and then euphoric when the deal finally closed.
One of the earliest chapters in the book is called 'Creative Survival.' It describes how David Cowper entered into the life insurance business and the early struggles he faced while trying to keep his career alive. I really identified with this chapter and was relieved to know that someone as successful as David Cowper wasn't always that way -- he went his first three months in the business without a single sale. Although it was tough for him he still kept his sense of humour. I'll always remember the exploding soup can story that saved his career.
The rest of the book outlines the strategies that David Cowper used to grow from his humble beginnings to becoming a founding member of Top of the Table. He really makes you believe that if he can do it so can you and I. And, more than that, he actually shows us how he did it. He explores in great depth the importance of both knowledge and passion in a life insurance agent's career. In fact, in one story he shows us how he won the confidence of the key player in a $42 million case, simply by pointing out the suicide clause in the insurance policies.
If you've ever wanted to know how to get tough prospects to start talking and trusting you and treating you like someone who can help them, you had better read David Cowper's strategy on disarming the prospect. This was the most important thing I learned in the book, and I have now changed the way I approach a prospect. Like David Cowper I tell my prospects that there is a good chance they won't need my services, which is difficult because I'm afraid of losing the business. But afterwards I find the prospect opens up to me and we are able to work together to solve whatever problems their business is facing.
In the last chapter, David Cowper makes the fantastic prediction that in the near future it will be possible for a life insurance agent to have a one billion dollar year. He makes this statement on the strength of five opportunities he sees for our business in the 21st century -- such as the knowledge worker market and the golden age of entrepreneurs. And believe me, those are five opportunities I'm definitely going to take advantage of.
Some very high-profile agents in our field who read advance copies of this book recommended it to me as "the best book on life insurance they have ever read." After reading it from cover to cover in just a couple of days I must absolutely agree. I will definitely apply David Cowper's Breakthrough strategies as I develop my own megacase business.
David Cowper's guide to success in sales begins as a sleek black limousine pulls to a curb. Once inside the limousine, Cowper has 15 minutes to close a deal and open the door to a $100 Million life insurance policy. As this scene suggests, Cowper's book is both an account of his own internationally renowned career and a guide to those seeking to follow in his footsteps. At once readable and perceptive, Breakthrough contains two key messages. The first is that "We don't earn a living, we learn a living." Cowper demonstrates conclusively that insurance professionals need solid knowledge of a prospect's own circumstances, of insurance products, and of relevant social, governmental, or business influences. In scene after scene, Cowper allows readers to watch as he puts his own knowledge to work in selling a variety of difficult cases. Cowper's second message is that persistence pays off. Closing multi-million dollar deals can require weeks, months, or even years of courting strong prospects. What does a sales professional do during this time? Cowper provides sales and marketing strategies to follow. He also recommends visualisation and focus as ways of maintaining the drive necessary to pursue cases over long periods of time. Breakthrough provides a model of success which is clear, readable, and filled with memorable detail. It offers sales professionals at all levels a rare opportunity to watch as a master salesman clinches deal after deal.
Can't ask for authors better than these...
The sections include Book of Mormon Studies, Old Testament Studies and Ancient History, and New Testament Studies and Early Christian History.
I got it for the article on Leroy Robertson's Oratorio from the Book of Mormon.
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The editors, as they note in the Introduction, provided very loose guidelines to the contributing essayists: Beyond refereeing the broad topics for inclusion, the editors largely gave carte blanche to the contributors regarding style and content. This "looseness of control" has resulted in a volume of both very considerable strengths (some of which I highlight here) and a few perplexing weaknesses and oversights which I allude to at the end of my comments.
The "logical bookends" of this volume are an opening essay by Leon Botstein, titled "Gustav Mahler's Vienna," and a closing essay by Wilfrid Mellers, titled "Mahler and the Great Tradition: Then and Now." The former sets the cultural, socio-political and philosophical stage of fin-de-siècle Vienna onto which Mahler entered, and the latter nicely summarizes how Mahler might fit into a continuum of musical composition and practice that preceded and succeeded him. (This new paperback edition also includes. at the end, two new essays, not present in the hardback edition, covering recollections of his daughter, Anna, and recently discovered Mahler "juvenilia" in the form early chamber music and songs.) In between these bookends, all of Mahler's music, and much about his life and times, and how he and his music were accepted (or not accepted) inside and outside Vienna, are covered.
The essays regarding Mahler's music are largely - and splendidly - informative, and provide alternative insights into the music not necessarily covered by the well-known analyses of Theodor Adorno, Constantin Floros and Henry-Louis de La Grange. (Interestingly, many of the music-analysis contributors reference Adorno's "Mahler: A Musical Physiognomy." Perhaps Adorno's time has come as well, some 40 years after his writing this difficult-but-epiphanic work.) But at least three of them are (to me, anyway) frustratingly idiosyncratic. Peter Franklin's essay on the Third Symphony ("A Stranger's Story: Programmes, Politics, and Mahler's Third Symphony") is heavy on largely-irrelevant minutiae and very light on certain matters of true import, such as the significance of the final Adagio of the work. David Matthews' "The Sixth Symphony," by his choice, largely limits his comments to the two well-known areas of conjecture/dispute: the ordering of the two inner (Scherzo, Andante) movements and the matter of whether the final movement should have two hammer blows or three. (I am personally in agreement with both of his choices, but that is largely beside the point.) And Colin Matthews' "The Tenth Symphony" is largely a technical analysis of the available raw materials of the work left by Mahler for realization by others but very little about what interests most Mahlerites regarding this final work: A detailed comparison of the various "performing versions" or "realizations" that exist.
Among the many personal "resonances" for me are the following: A finely-crafted analysis of Mahler's "Opus 1," his "Das klagende Lied" (but absent the fact that a splendid recording of the 1997-discovered Ur-text score has been made by Kent Nagano); (finally) a musicological connection between Mahler and Hector Berlioz, by way of how the widely-separated octaves (of trombone pedal tones and high flutes) in the "Hostias" of the Berlioz Requiem might have influenced Mahler when he was composing the first "Nachtmusik" movement of his Seventh Symphony; and a fascinating footnote to the analysis of the final Adagio of the Ninth Symphony, where some apparently reliable documentation is provided for Mahler's awareness of the famous hymn, "Abide with Me," the tune that always comes to mind every time I listen to this gorgeous hymn-like passage.
Elsewhere (and scattered throughout various essays) are frequent allusions to certain parallels between Mahler and Charles Ives. (They both wrote "music about music," incorporated "vernacular" music in their works, were almost-simultaneous "polytonalists" and of course contemporaries. The matter of whether Mahler had been aware of the music of Ives is put more in the affirmative than I've seen heretofore; hopefully this is the result of recent research about which there is more to follow.) Similarly, there are frequent parallels drawn between Mahler and Dmitri Shostakovich; the case for Shostakovich being the logical (and most significant by far) successor to Mahler is well-drawn without overlooking the obvious differences between them.
There is an intriguing chapter on some not-so-obvious parallels between Mahler and Debussy (although the overt pentatonicism of "late" Mahler is made elsewhere, most obviously in the essay on "Das Lied von der Erde"). And, for me, one of the best contributions is by Edward R. Reilly, in his essay on "Mahler in America."
The volume is exceedingly well-annotated, with liberal footnotes (many, such as the "Abide with Me" one, of considerable length), and, at the back, a full bibliography of source materials, a detailed index of works, and a general index as well. Clearly, a lot of work (both scholarship and "routine editorial") has gone into the preparation of this valuable resource.
The book is not perfect in all respects, at least from my own personal point of view. Biographical details are not its strength, but there are the volumes by La Grange and Blaukopf & Blaukopf to compensate. (Nonetheless, I would have liked to have seen a contribution by Herta Blaukopf, who is as knowledgeable about Mahler's Vienna Conservatory period as any.) But, as I noted at the outset, its very considerable strengths greatly outweigh its relatively minor weaknesses. If you consider yourself a Mahlerite, this book belongs in your library, alongside your copies of Adorno, Blaukopf, Floros and La Grange.
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I gave it three stars because most reviewers are far to liberal with their stars. To me 3 stars means worth buying, 4 means a must buy, and 5 means it'll be a classic for a long time.
I equate this book to Mallet's "A Wavelet Tour of Signal Processing". The subject matter is slightly different, but both are very readable.
for time series analysts. It goes very deep within the applied
side of wavelet analysis on real time series while not compromising
the mathematical side. A lot of books and papers insist too much
on the mathematical side of wavelets while this one provides just
the right balance between rigor and practical insight. If your
interest does not lie in maths but just in wavelets as a tool,
stick to this one.
As a bonus, it contains a lot of exercices along with answers
at the end of the book...a very good textbook indeed...
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I recommend this book to people who like to read cooking books as well as a mystery story. If you get hungry as you read a cooking book, I recommend that you should not read it. It has lots of good recipes.
This book was the textbook used at the University of Wisconsin-Madison for the graduate course in Bayesian Decision and Control I during the fall of 2001 and 2002. It strikes a good balance between theory and practical example, making it ideal for a first course in Bayesian theory at an intermediate-advanced graduate level. Its emphasis is on Bayesian modeling and to some degree computation.
Prerequisites
While no Bayesian theory is assumed, it is assumed that the reader has a background in mathematical statistics, probability and continuous multi-variate distributions at a beginning or intermediate graduate level. The mathematics used in the book is basic probability and statistics, elementary calculus and linear algebra.
Intended audience
This book is primarily for graduate students, statisticians and applied researchers who wish to learn Bayesian methods as opposed to the more classical frequentist methods.
Material covered
It covers the fundamentals starting from first principles, single-parameter models, multi-parameter models, large sample inference, hierarchical models, model checking and sensitivity analysis, study design, regression models, generalized linear models, mixture models and models for missing data. In addition it covers posterior simulation and integration using rejection sampling and importance sampling. There is one chapter on Markov chain simulation (MCMC) covering the generalized Metropolis algorithm and the Gibbs sampler.
Over 38 models are covered, 33 detailed examples from a wide range of fields (especially biostatistics). Each of the 18 chapter has a bibliographic note at the end. There are two appendixes: A) a very helpful list of standard probability distributions and B) outline of proofs of asymptotic theorems.
Sixteen of the 18 chapters end with a set of exercises that range from easy to quite difficult. Most of the students in my fall 2001 class used the statistical language R to do the exercises.
The book's emphasis is on applied Bayesian analysis. There are no heavy advanced proofs in the book. While the proofs of the basic algorithms are covered there are no algorithms written in pseudo code...Additional books of related interest
1) Statistical Decision Theory and Bayesian Analysis, James Berger, second edition. Emphasis on decision theory and more difficult to follow than Gelman's book. Covers empirical and hierarchical Bayes analysis. More philosophical challenging than Gelman's book.
2) Monte Carlo Statistical Methods, Robert and Casella. Very mathematically oriented book. Does a good job of covering MCMC.
3) Monte Carlo Methods in Bayesian Computation, Ming-Hui Chen, Qi-Man Shao, Joseph George Ibrahim. An enormous number of algorithms related to MCMC not covered elsewhere. If you need MCMC and need an algorithm to implement MCMC this is the book to read.
4) Monte Carlo Strategies in Scientific Computing, Jun S. Liu. Covers a wide range of scientific disciplines and how Monte Carlo methods can be used to solve real world problems. Includes hot topics such as bioinformatics. Very concise. Well written, but requires effort to understand as so many different topics are covered. This book is my most often borrowed book on Monte Carlo methods. Jun S. Liu is a big gun at Harvard.
5) Probabilistic Networks and Expert Systems. Cowell, Dawid, Lauritzen, Spiegelhalter. Covers the theory and methodology of building Bayesian networks (probabilistic networks).