spc(zipfR)
spc()所属R语言包：zipfR
Frequency Spectra (zipfR)
频谱（zipfR）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
In the zipfR library, spc objects are used to represent a word frequency spectrum (either an observed spectrum or the expected spectrum of a LNRE model at a given sample size).
在zipfR图书馆，spc对象被用来表示一个字的频谱（无论是一个观察到的频谱或预期频谱一个LNRE模型在给定采样大小）。
With the spc constructor function, an object can be initialized directly from the specified data vectors. It is more common to read an observed spectrum from a disk file with read.spc or compute an expected spectrum with lnre.spc, though.
spc构造函数，可以直接初始化一个对象从指定的数据向量。这是比较常见的观测谱从磁盘文件读read.spc或计算的预期光谱lnre.spc，虽然。
spc objects should always be treated as read-only.
spc对象应始终被视为只读。
用法----------Usage----------
spc(Vm, m=1:length(Vm), VVm=NULL, N=NA, V=NA, VV=NA,
m.max=0, expected=!missing(VVm))
参数----------Arguments----------
参数：m
integer vector of frequency classes m (if omitted, Vm is assumed to list the first k frequency classes V_1, …, V_k)
整数向量的频度等级m（如果省略，Vm假设列出的第一个k的频度等级V_1, …, V_k）
参数：Vm
vector of corresponding class sizes V_m (may be fractional for expected frequency spectrum E[V_m])
向量的相应的班级规模V_m（可能是小数预期频谱E[V_m]）
参数：VVm
optional vector of estimated variances Var[V_m] (for expected frequency spectrum only)
可选的向量的估计方差Var[V_m]（预期频谱）
参数：N, V
total sample size N and vocabulary size V of frequency spectrum. While these values are usually determined automatically from m and Vm, they are required for an incomplete frequency spectrum that does not list all non-empty frequency classes.
总样本量N和词汇量的大小V频谱。虽然这些值通常是自动确定m和Vm，他们都需要一个不完整的频谱，并没有列出所有非空频度等级。
参数：VV
variance Var[V] of expected vocabulary size. If VVm is specified, VV should also be given.
方差Var[V]预期的词汇量的大小。如果VVm指定，VV应该也可以。
参数：m.max
highest frequency class m listed in incomplete spectrum. If m.max is set, N and V also have to be specified, and all non-zero frequency classes up to m.max have to be included in the input vectors. Frequency classes above m.max in the input will automatically be deleted.
频率最高的类m中列出不完整的光谱。 m.max如果设置，N和V也有规定，所有非零频度等级高达m.max必须被包含在输入向量。上述的m.max的频率类的输入将被自动删除。
参数：expected
set to TRUE if the frequency spectrum represents expected values E[V_m] of the class sizes according to some LNRE model (this is automatically triggered when the VVm argument is specified).
设置为TRUE的频谱的代表预期值E[V_m]之类的尺寸根据一些LNRE模型（这是自动触发时，VVm指定参数）。
Details
详细信息----------Details----------
A spc object is a data frame with the following variables:
Aspc对象是一个数据框以下因素：
m frequency class m, an integer vector
m频率类m，一个整数向量
Vm class size, i.e. number V_m of types in frequency class m (either observed class size from a sample
Vm每班学生人数，即V_m类型的频度等级m（无论是观察到的班级规模从样本
VVm optional: estimated variance V[V_m] of expected class size (only meaningful for expected spectrum derived
VVm可选：估计方差V[V_m]预期的班级规模（唯一有意义的预期光谱而得
The following attributes are used to store additional information about the frequency spectrum:
以下属性的频谱，用于存储其他信息：
m.max if non-zero, the frequency spectrum is
m.max如果不为零，频谱
N, V sample size N and vocabulary size V of the frequency spectrum. For a complete frequency spectrum, these values could easily be determined from m and
N, V样本大小N和词汇量的大小V频谱。对于一个完整的频谱，这些值可以很容易地确定m和
VV variance of expected vocabulary size; only present if hasVariances is TRUE. Note that VV may
VV方差的预期词汇量的大小; hasVariances如果TRUE。需要注意的是VV可能
expected if TRUE, frequency spectrum lists expected class sizes E[V_m] (rather than observed sizes V_m). Note that the VVm variable is only
expected如果TRUE，频谱列出预期的班级规模E[V_m]（而不是观察到的尺寸V_m）。需要注意的是VVm变量是唯一的
hasVariances indicates whether or not the VVm
hasVariances表示是否VVm
值----------Value----------
An object of class spc representing the specified frequency spectrum. This object should be treated as read-only (although such behaviour cannot be enforced in R).
对象的类spc指定的频谱。这个对象应该被视为只读（虽然这种行为不能被强制执行，在R）。
参见----------See Also----------
read.spc, write.spc, spc.vector, sample.spc, spc2tfl, tfl2spc, lnre.spc, plot.spc
read.spc，write.spc，spc.vector，sample.spc，spc2tfl，tfl2spc，lnre.spc，plot.spc
Generic methods supported by spc objects are print, summary, N, V, Vm, VV, and VVm.
支持的spc对象的通用方法是print，summary，N，V，Vm，VV和VVm。
Implementation details and non-standard arguments for these methods can be found on the manpages print.spc, summary.spc, N.spc, V.spc, etc.
这些方法的执行细节及非标参数上可以找到的手册页print.spc，summary.spc，N.spc，V.spc，等
实例----------Examples----------
## load Brown imaginative prose spectrum and inspect it[＃加载布朗的想象力的散文谱和检查]
data(BrownImag.spc)
summary(BrownImag.spc)
print(BrownImag.spc)
plot(BrownImag.spc)
N(BrownImag.spc)
V(BrownImag.spc)
Vm(BrownImag.spc,1)
Vm(BrownImag.spc,1:5)
## compute ZM model, and generate PARTIAL expected spectrum[＃计算ZM模型，并产生部分频谱]
## with variances for a sample of 10 million tokens[＃10万元标记的样本方差]
zm <- lnre("zm",BrownImag.spc)
zm.spc <- lnre.spc(zm,1e+7,variances=TRUE)
## inspect extrapolated spectrum[＃检查推断谱]
summary(zm.spc)
print(zm.spc)
plot(zm.spc,log="x")
N(zm.spc)
V(zm.spc)
VV(zm.spc)
Vm(zm.spc,1)
VVm(zm.spc,1)
## generate an artificial Zipfian-looking spectrum[＃产生一个人工Zipfian好看的频谱]
## and take a look at it[＃看看它]
zipf.spc <- spc(round(1000/(1:1000)^2))
summary(zipf.spc)
plot(zipf.spc)
## see manpages of lnre, and the various *.spc mapages[＃请参阅联机帮助页lnre，各种*。SPC mapages]
## for more examples of spc usage[＃更多的例子使用的SPC]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-2 07:50:16
