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Usually ships within 2 to 3 days. From Europe's No. Meanwhile, Renko is falling in love with a beautiful, headstrong dissident for whom he may risk everything. When the corpse of a Russian is hauled from the oily waters of Havana Bay, Arkady Renko comes to Cuba to identify the body. Looking for the killer, he discovers a city of faded loneliness, unexpected danger, and bewildering contradictions. His investigation introduces him to a beautiful Cuban policewoman; to the rituals of Santeria; to an American fugitive and a group of ruthless mercenaries.
In this place where all things Russian are despised, where Hemingway fished and the KGB flourished, where the hint of music is always in the air, Arkady finds a trail of deceit that reaches halfway around the world—and a reason to relish his own life again.
In his groundbreaking Gorky Park, Martin Cruz Smith created an iconic detective of contemporary fiction. Quietly subversive, brilliantly analytical, and haunted by melancholy, Arkady Renko survived, barely, the journey from the Soviet Union to the New Russia, only to find his transformed nation just as obsessed with corruption and brutality as was the old Communist dictatorship.
It is still aglow with radioactivity, now inhabited only by the militia, shady scavengers, a few reckless scientists, and some elderly peasants who refuse to relocate. A story that takes place on a train. About building a world out of matchsticks. About brothers. About drinking. About things that matter.
This meeting brought together leading researchers in high-energy physics to exchange the latest ideas in QCD and gauge theories at strong coupling at large. It honored the 60th birthday of Professor Arkady Vainshtein, and the papers included in this proceedings volume also look back on the history of the subjects in which Arkady played such a central role: applications of PCAC, penguins, invisible axions, QCD sum rules, exact beta functions, condensates in supersymmetry, powerful heavy quark expansions, and new anomalies in 2D SUSY theories.
The current status of these subjects was summarized in several excellent presentations that also outlined a historical perspective. Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods prior and posterior , Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence.
This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation.
The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. Subject: good article on Data Migration and Data Quality. Conversion from an existing data source almost never goes smoothly and takes the better half of the new system implementation effort.
I remember well an HR executive confidently telling me over lunch that because his company was implementing a modern HR and payroll system, it would no longer have data quality problems. How could I respond? In fact, they are about to get much bigger. I still vividly remember one of my first major data conversion projects. I was on a team implementing a new pension administration system.
We needed to convert employee compensation data from the legacy HR database. The old data was stored in much detail—by paycheck and compensation type.
The new database simply needed aggregate monthly pensionable earnings. The mapping was trivial: take all records with relevant compensation types provided as a list of valid codes , total the amounts for each calendar month, and place the result into the new bucket.
The Reality The result was disastrous. Half of the sample records I looked at did not match the summary reports printed from the old system. A meeting was called for the next morning, and in the wee hours of that night, I had the presence of mind to stop looking for bugs in the code and to poke into the source data.
The data certainly did not add up to what was showing on the summary reports, yet the reports were produced from these very data. This mathematical puzzle kept me up until dawn. By then, I had most of it figured out. Our list was missing half a dozen compensation codes included in the aggregate amounts.
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