与 «R&»相关的马来语书籍
在以下的参考文献中发现
R&的用法。与
R&相关的书籍以及同一来源的简短摘要提供其在 马来语文献中的使用情境。
This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems.
2
A Textbook of Graph Theory
Here is a solid introduction to graph theory, covering Dirac's theorem on k-connected graphs, Harary-Nashwilliam's theorem on the hamiltonicity of line graphs, Toida-McKee's characterization of Eulerian graphs, Fournier's proof of ...
R. Balakrishnan, K. Ranganathan, 2000
3
R for SAS and SPSS Users
Introduces R, a free software system for data analysis and graphics with over 4.000 add-on packages. Demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions.
4
R and Data Mining: Examples and Case Studies
Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and ...
5
An R Companion to Applied Regression
This is a broad introduction to the R statistical computing environment in the context of applied regression analysis.
John Fox, Sanford Weisberg, 2010
This highly practical book is written specifically for those involved with commercial cheesemaking - either directly or as ingredient or equipment suppliers.
R. Scott, Richard K. Robinson, R. Andrew Wilbey, 1998
7
Applied Econometrics with R
This is the first book on applied econometrics using the R system for statistical computing and graphics.
Christian Kleiber, Achim Zeileis, 2008
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently.
9
The First R: How Children Learn Race and Racism
A remarkable study revealing that answers might be more startling than could be imagined.
Debra Van Ausdale, Joe R. Feagin, 2001
10
Generalized additive models: an introduction with R
Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and related advanced models, enabling informed use of these very flexible tools.
