After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics.
Call for proposals for writing a book about R (via Chapman & Hall/CRC) | R-statistics blog
These chapters cover the simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo MCMC methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions.
- Bomber Squadron No 7: The World War II Record.
- Statistical Computing with R - CRC Press Book?
- Maria Rizzo — Home;
Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing. Table Of Content Introduction.
Покупки по категориям
Probability and Statistics Review. Methods for Generating Random Variables. Visualization of Multivariate Data.
Monte Carlo Integration and Variance Reduction. Monte Carlo Methods in Inference. Extending the Linear Model with R: Springer Series in Statistics and Computing. Modern Applied Statistics with S.
- CAPO?
- The Blackthorn Conspiracy.
- Popular Searches.
A Beginner's Guide to R. A language for data analysis and graphics. Journal of Computational and Graphical Statistics , 5 3: We have a brief tutorial available on how to read data into R.
Call for Proposals for The R Series from Chapman & Hall/CRC
Can I use R without having to learn the details of the R language? Yes at least for the basics , there are a number of "front ends" that have been constructed in order to make it easier for users to interact with the R statistical computing environment. For example, a graphical user interface or "GUI" allows the analyst to carry out data analysis tasks by selecting items from menus and lists, rather than entering commands. The R Commander is accessed by installing and loading the Rcmdr package within R. The R Commander provides an easy-to-use, menu-based system for loading data into R, manipulating data values, performing statistical analyses, creating graphical displays, and carrying out diagnostic tests on statistical models.
Documentation for the R Commander is available on John Fox's website and in the following paper:. The advantage provided by the R Commander or another GUI is that the user does not need to learn a language in order to carry out his or her analysis. Instead, each step is taken by making one or more selections from a menu of available options. The disadvantage of interacting with the R environment through a GUI is that the course of the analysis is limited to those actions that have been programmed into the GUI.
What is R? How do I use it?
Thus, one could argue that using a GUI removes much of the flexibility that is inherent in the R environment. In order to overcome the preceding limitation, the R Commander and most other GUIs allow the user to employ both methods of interacting with the environment within a single R session. For example, one could invoke the R Commander , and use its GUI to read the contents of an external file and create an R data frame.