Download PDF by Rossiter: Introduction to the R Project for Statistical Computing

By Rossiter

Show description

Read or Download Introduction to the R Project for Statistical Computing PDF

Best mathematical & statistical books

Download PDF by John Gray: Mastering Mathematica®. Programming Methods and Applications

This article addresses using Mathematica as a symbolic manipulator, a programming language and a normal device for wisdom illustration. additionally integrated is insurance of practical programming, rule-based programming, procedural programming, object-oriented programming and images programming

Phillip Backley's An Introduction to Element Theory PDF

A clean substitute for describing segmental constitution in phonology. This ebook invitations scholars of linguistics to problem and think again their latest assumptions concerning the kind of phonological representations and where of phonology in generative grammar. It does this by means of delivering a accomplished advent to point conception.

Download e-book for iPad: Matrix Algorithms in MATLAB by Ong U. Routh

Matrix Algorithms in MATLAB specializes in the MATLAB code implementations of matrix algorithms. The MATLAB codes awarded within the e-book are verified with hundreds of thousands of runs of MATLAB randomly generated matrices, and the notation within the publication follows the MATLAB kind to make sure a tender transition from formula to the code, with MATLAB codes mentioned during this booklet saved to inside of a hundred traces for the sake of readability.

Additional resources for Introduction to the R Project for Statistical Computing

Example text

5 ... 1 ... : 1 1 ... frame’: 50 obs. 6 5 ... 4 ... 4 ... 3 ... : 1 1 ... frame’: 50 obs. 9 ... 4 ... 3 ... 6 1 ... : 2 2 ... frame’: 50 obs. 3 ... 5 ... 3 ... 8 ... : 3 3 ... The split method builds a list of data frames named by the level of the factor on which the original data frame was split. Here the original 34 150 observations have been split into three lists of 50, one for each species. Length) Min. 1st Qu. Median Mean 3rd Qu. 10 Max. 90 Simultaneous operations on subsets We often want to apply some computation to all subsets of a data frame.

It is informative but not so attractive. We can customize the plotting symbol (pch argument), its colour and size (col and cex arguments), the axis labels (xlab and ylab arguments), and graph title (main argument). g. "*" for an asterisk) or an integer code for one of a set of graphics symbols. Figure 3 shows the symbols and their codes. Note that symbols 21–26 also have a fill (background) colour, specified by the bg argument; the main colour specified by the col argument specifies the border.

Frame’: 31 obs. 8 11 11 ... $ Height: num 70 65 63 72 81 83 66 75 80 75 ... 6 ... > summary(trees$Volume) Min. 1st Qu. Median Mean 3rd Qu. Max. 0 As the example shows, some methods (like summary()) can deal with NA’s, but others can’t. frame’: 30 obs. 8 11 11 ... $ Height: num 65 63 72 81 83 66 75 80 75 79 ... 6 ... The first observation, with the missing volume, was removed. 24 Control structures and looping S is a powerful programming language with Algol-like syntax25 and control structures. Single statements may be grouped between the braces { and }, separated either by new lines or the command separator ;.

Download PDF sample

Introduction to the R Project for Statistical Computing by Rossiter


by James
4.1

Rated 4.53 of 5 – based on 9 votes