http://www.commres.net/ 2026-04-17T09:54:14+00:00 http://www.commres.net/ http://www.commres.net/_media/wiki/logo.png text/html 2020-03-09T10:14:53+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/basics?rev=1583748893&do=diff Print > pi [1] 3.141593 > sqrt(2) [1] 1.414214 When you enter expressions like that, R evaluates the expression and then implicitly calls the print function. So the previous example is identical to this: > print(pi) [1] 3.141593 > print(sqrt(2)) [1] 1.414214 $$ r = \frac {\text{covariance (x, y)}} {sd(x) * sd(y)} $$ text/html 2020-05-26T08:40:53+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/data_structures?rev=1590482453&do=diff DATA Vectors * 벡터 * Vectors are homogeneous: All elements of a vector must have the same type. * Vectors can be indexed by position: v[2] refers to the second element of v. * Vectors can be indexed by multiple positions, returning a subvector: v text/html 2020-03-09T10:18:17+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/data_transformations?rev=1583749097&do=diff > v <- c(40,2,83,28,58) > f <- factor(c("A","C","C","B","C")) Splitting a Vector into Groups > library(MASS) Warning message: 패키지 ‘MASS’는 R 버전 3.2.5에서 작성되었습니다 > split(Cars93$MPG.city, Cars93$Origin) # Origin별로 MPG.city를 나눠라 $USA [1] 22 19 16 19 16 16 25 25 19 21 18 15 [13] 17 17 20 23 20 29 23 22 17 21 18 29 [25] 20 31 23 22 22 24 15 21 18 17 18 23 [37] 19 24 23 18 19 23 31 23 19 19 19 28 $`non-USA` [1] 25 18 20 19 22 46 30 24 42 24 29 22 [13] 26 20 17 18 18 29 28 26 18 17 20 19 [25] 29 1… text/html 2020-03-09T10:19:42+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/general_statistics?rev=1583749182&do=diff Null Hypotheses, Alternative Hypotheses, and p-Values 9.1. Summarizing Your Data library(MASS) # to include Cars93 data > summary(Cars93$Manufacturer) Acura Audi BMW Buick 2 2 1 4 Cadillac Chevrolet Chrylser Chrysler 2 8 1 2 Dodge Eagle Ford Geo 6 2 8 2 … text/html 2020-03-17T17:48:10+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/getting_started?rev=1584467290&do=diff Installation, base Windows * Open <http://www.r-project.org/> in your browser. * Click on “CRAN”. You’ll see a list of mirror sites, organized by country. * Select a site near you. * Click on “Windows” under “Download and Install R”. * Click on “base”. text/html 2020-03-09T10:21:12+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/graphics?rev=1583749272&do=diff Notes on Graphics Functions It is important to understand the distinction between high-level and low-level graphics functions. A high-level graphics function starts a new graph. It initializes the graphics window (creating it if necessary); sets the scale; maybe draws some adornments, such as a title and labels; and renders the graphic. Examples include: text/html 2020-03-09T10:16:47+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/input_output?rev=1583749007&do=diff A Philosophical Note on R input system Several of my Statistical Analysis System (SAS) friends are disappointed with the input facilities of R. They point out that SAS has an elaborate set of commands for reading and parsing input files in many formats. R does not, and this leads them to conclude that R is not ready for real work. After all, if it can’t read your data, what good is it? text/html 2020-03-09T10:16:07+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/navigating?rev=1583748967&do=diff Working Directory Getting > getwd() [1] "/home/paul/research" > setwd("Bayes") > getwd() [1] "/home/paul/research/Bayes" setwd("c:/r_data") getwd() Saving Workspace > save.image() Command History > history() # Default 25 > history(100) # Show 100 most recent lines of history > history(Inf) # Show entire saved history text/html 2025-09-16T23:22:15+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/b/r_cookbook/probability?rev=1758064935&do=diff Normal distribution functions Function Purpose dnorm Normal density pnorm Normal distribution function qnorm Normal quantile function rnorm Normal random variates Table 8-1. Discrete distributions Discrete distribution R name $ f(x) = \frac{1}{\sigma \sqrt{2\pi}} e^{\frac{-(x-\mu)^2}{2\sigma^2}} $$t = \frac{Z}{\sqrt{\frac{V}{m}}}$$$n!/r!(n − r)!$$