统计代码银行StatCodeBank

It’s not possible to directly measure an abstract concept like intelligence, but it is possible to measure performance on different tests. You could use factor analysis to analyze a set of test scores (the observed values) to try to determine intelligence (the hidden value).

Factor analysis is available in R through the function factanal in the stats package:

factanal(x, factors, data = NULL, covmat = NULL, n.obs = NA,
         subset, na.action, start = NULL,
         scores = c("none", "regression", "Bartlett"),
         rotation = "varimax", control = NULL, ...)

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This returns a vector with the minimum and maximum value:

> range(dow30$Open)
[1]   0.99 122.45

Another useful function is quantile. This function can be used to return the values at different percentiles (specified by the probs argument):

> quantile(dow30$Open, probs=c(0,0.25,0.5,0.75,1.0))
     0%     25%     50%     75%    100%
  0.990  19.655  30.155  51.680 122.450

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4.5.1. Creating a Package Directory

To build a package, you need to place all of the package files (code, data, documentation, etc.) inside a single directory. You can create an appropriate directory structure using the R function package.skeleton:

package.skeleton(name = "anRpackage", list,
                 environment = .GlobalEnv,
                 path = ".", force = FALSE, namespace = FALSE,
                 code_files = character())

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3.8. Getting Help

> help(glm)

or, equivalently:

> ?glm

To search for help on an operator, you need to place the operator in backquotes:

> ?`+`

If you’d like to try the examples in a help file, you can use the example function to automatically try them. For example, to see the example for glm, type:

> example(glm)

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Array

a <- array(c(1,2,3,4,5,6,7,8,9,10,11,12),dim=c(3,4))

> a
     [,1] [,2] [,3] [,4]
[1,]    1    4    7   10
[2,]    2    5    8   11
[3,]    3    6    9   12

a vector with the same contents:

> v <- c(1,2,3,4,5,6,7,8,9,10,11,12) > v [1] 1 2 3 4 5 6 7 8 9 10 11 12

matrix is just a two-dimensional array:

> m <- matrix(data=c(1,2,3,4,5,6,7,8,9,10,11,12),nrow=3,ncol=4)
> m
     [,1] [,2] [,3] [,4]
[1,]    1    4    7   10
[2,]    2    5    8   11
[3,]    3    6    9   12

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