LiteRatuRa

[Aleksandar Blagotić]

Ukoliko imate predloge za zanimljivu literaturu u vezi sa R-om, evo teme za to. Biće obeležena, tako da je možete lakše naći. Svi linkovi i/ili attachment-i su dobrodošli dokle god ne krše autorska prava.

Hvala unapRed!

[Aleksandar Blagotić]

Posto sam resio da budem revnosan i organizovan (nesto me krenulo od jutros), knjige koje toplo preporucujem su:

• Burns, P. - The R Inferno [pdf]
  
• Paradis, E. - R for Beginners [pdf]
• Maindonald, J.H. - Using R for Data Analysis and Graphics [pdf]
• Chambers, J. (2010). Software for Data Analysis: Programming with R. Springer. [amazon]
• Venables, W., & Ripley, B. D. (2011). S Programming. Springer. [amazon]
• Dalgaard, P. (2008). Introductory Statistics with R (2nd ed.). Springer. [amazon]
• Spector, P. (2008). Data Manipulation with R (1st ed.). Springer. [amazon]

I dalje stojim iza toga da je "Inferno" najbolja "dz" knjiga o R-u. Koncizna, pragmaticna, ali mozda i nije najsjajnije resenje za pocetnike. Paradis-ova knjiga je prva koju sam procitao o R-u, a odmah zatim i Maindonald-a. Za pocetni nivo vise nego dovoljno. Dalgaard takodje. Najpragmaticnija, po meni je Spector-ova, a Chambers i Venables & Ripley su svakako crème de la crème i preporucujem svima koji zele da zaista nauce R.

[Santic, Srdjan]

Ja bih još dodao “R Cookbook” od Teetor-a, kao i “The Art of R Programming” od Matloff-a…

 

E sad, ko ne zna ni statistiku ni R, a želi da nauči i jedno i drugo (R u smislu analize, ne programiranja), svesrdno preporučujem Field & Miles “Discovering Statistics Using R”.

 

 

Srdjan Šantić M.A. Marketing Assistant Nielsen Audience Measurement Serbia Gavrila Principa 8 Belgrade Phone +381 11 3284 510 Fax       +381 11 3288 205 www.agbnielsen.com Please consider the environment before printing this email

[Jovan Njegic]

Dodao bih literaturu za analizu vremenskih serija, koristim je u finansijama:

Paul S.P. Cowpertwait · Andrew V. Metcalfe, 2009, Introductory Time Series with R (Use R!)
Stefano M. Iacus, 2011, Option Pricing and Estimation of Financial Models with R
Jonathan D. Cryer • Kung-Sik Chan, 2008, Time Series Analysis With Applications in R
Julian J.Faraway, 2005, Linear Models with R
Peter Dalgaard, 2008,Introductory Statistics with R
Yosef Cohen, Jeremiah Y. Cohen, 2008, Statistics and Data with R: An applied approach through examples

Posebno bih preporucio - odlicna knjiga, sa kompletnom podrskom na sajtu profesora Tsay-a:

RUEY S. TSAY ,2010, Analysis of Financial Time Series

[mr.stefi]

Da nemaš slučajno i linkove za download ovih knjiga?

Puno pozdrava,

Stefan

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[Aleksandar Blagotić]

Samo Vas molim da ne postavljate linkove ka "alternativnim" nacinima preuzimanja licencirane literature!

Hvala

aL3xa

2013/5/16 mr.stefi <mr.s...@gmail.com>

[mr.stefi]

Meni na private... :)

[mr.stefi]

Evo jedne nove knjige koju su najavili na R-bloggers:

"Practical Data Science with R"

http://www.r-bloggers.com/big-news-practical-data-science-with-r-meap-launched/

Pozdrav,

Stefan

2013/5/16 Aleksandar Blagotić <aca.bl...@gmail.com>

[Vladimir]

- ZA POČTNIKE: PREDJELO - :)

"This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming."

Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines. 

Da ne kačim ovde link ka piratskim sajtovima, svi koji žele knjigu koja je opisana redovima iznad ovog, mogu me kontaktirati na PP.

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