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using R for data analyse.tmp

'using R for data analyse.tmp'
An Introduction to R Notes on R: A Programming Environment for Data Analysis and Graphics Version 2.11.1 (2010-05-31) W. N. Venables, D. M. Smith and the R Development Core Team Copyright c ? 1990 W. N. Venables Copyright c ? 1992 W. N. Venables numbers and vectors. 7 2.1Vectors and assignment 7 2.2Vector arithmetic 7 2.3Generating regular sequences 8 2.4Logical vectors 9 2.5Missing values. 9 2.6Character vectors 10 2.7Index vectors; selecting and modifying subsets of a data set . 10 2.8Other types of objects 11 3Objects, their modes and attributes 13 3.1Intrinsic attributes: mode and length . 13 3.2Changing the length of an object . 14 3.3Getting and setting attributes 14 3.4The class of an object 14 4Ordered and unordered factors 16 4.1A specific example 16 4.2The function tapply() and ragged arrays. 16 4.3Ordered factors 17 5Arrays and matrices . 18 5.1Arrays . 18 5.2Array indexing. Subsections of an array 18 5.3Index matrices . 19 5.4The array() function 20 5.4.1Mixed vector and array arithmetic. The recycling rule 20 5.5The outer product of two arrays 21 5.6Generalized transpose of an array. 21 5.7Matrix facilities 22 5.7.1Matrix multiplication 22 ii 5.7.2Linear equations and inversion. 22 5.7.3Eigenvalues and eigenvectors. 23 5.7.4Singular value decomposition and determinants 23 5.7.5Least squares fitting and the QR decomposition 23 5.8Forming partitioned matrices, cbind() and rbind() 24 5.9The concatenation function, c(), with arrays . 24 5.10Frequency tables from factors 25 6Lists and data frames 26 6.1Lists . 26 6.2Constructing and modifying lists . 26 6.2.1Concatenating lists 27 6.3Data frames 27 6.3.1Making data frames . 27 6.3.2attach() and detach() . 27 6.3.3Working with data frames . 28 6.3.4Attaching arbitrary lists . 28 6.3.5Managing the search path . 29 7Reading data from files 30 7.1The read.table() function 30 7.2The scan() function . 31 7.3Accessing builtin datasets 31 7.3.1Loading data from other R packages . 31 7.4Editing data . 32 8Probability distributions. 33 8.1R as a set of statistical tables. 33 8.2Examining the distribution of a set of data . 33 8.3One- and two-sample tests 36 9Grouping, loops and conditional execution. 40 9.1Grouped expressions 40 9.2Control statements . 40 9.2.1Conditional execution: if statements 40 9.2.2Repetitive execution: for loops, repeat and while 40 10Writing your own functions 42 10.1Simple examples 42 10.2Defining new binary operators. 43 10.3Named arguments and defaults 43 10.4The ‘.’ argument . 44 10.5Assignments within functions 44 10.6More advanced examples 44 10.6.1Efficiency factors in block designs. 44 10.6.2Dropping all names in a printed array 45 10.6.3Recursive numerical integration. 45 10.7Scope. 46 10.8Customizing the environment 48 10.9Classes, generic functions and object orientation . 48 iii 11Statistical models in R . 50 11.1Defining statistical models; formulae. 50 11.1.1Contrasts 52 11.2Linear models. 53 11.3Generic functions for extracting model information 53 11.4Analys
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