plots(sac)
plots()所属R语言包：sac
Visualized Model Diagnostic and Loglikelihood Plot
可视化模型诊断和Loglikelihood的图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Plot and compare the empirical likelihood and semiparametric empirical
图和比较的经验似然和半参数经验
用法----------Usage----------
Graf.Diagnostic(x, k, m, Alpha, Beta, Color, LTY, xlab = "x",
ylab = "Estimated DF's", main = "Model Diagnostic",
OneLegend = TRUE, lgnd1, lgnd2, arw1, arw2, ...)
Plot.ll(x, ll, col, xaxis.lab = NULL, xlab = "k", ylab = "Loglikelihood",
main = "Plot of Loglikelihood",...)
参数----------Arguments----------
参数：x
a numeric vector or matrix containing the data, one row per observation;
包含的数据，每一个行观察的一个数值向量或矩阵;
参数：ll
loglikelihood function, output of SemiparChangePoint
loglikelihood功能，输出SemiparChangePoint
参数：col
color code or character string for the loglikelihood curve
颜色代码字符串的loglikelihood曲线的
参数：xaxis.lab
a vector of character strings or numeric values to be placed at the tickpoints as labels of axis
的字符串或数字值的矢量作为labelsaxis放在tickpoints在
参数：k
the estimated change-point, output of SemiparChangePoint
估计变点，输出SemiparChangePoint
参数：m
= n, the sample size, for "one-change" alternative, or the estimated second change-point for "epidemic" alternative, an output of SemiparChangePoint
=n，样本大小，"one-change"替代，或估计第二个变化点"epidemic"替代，输出SemiparChangePoint的
参数：Alpha
estimated parameter alpha, output of SemiparChangePoint
估计参数alpha，SemiparChangePoint输出
参数：Beta
estimated parameter beta, output of SemiparChangePoint
估计参数beta，SemiparChangePoint输出
参数：Color
a vector of character strings or color codes for curves of estimated distribution functions F-hat, F-tilde, G-hat and G-tilde
估计分布函数曲线的向量的字符串或颜色代码F-hat，F-tilde，G-hat和G-tilde
参数：LTY
vector of lty's, LTY=c(lty1, lty2, lty3, lty4), corresponds to the above color codes
矢量的LTY之，LTY = C（lty1 lty2，lty3，lty4），对应于上述的颜色代码
参数：xlab
character string for x-axis lable
x轴拉布勒字符串
参数：ylab
character string for y-axis lable
字符串为y轴LABLE
参数：main
character string for main title
主标题字符串
参数：OneLegend
a logical indicating whether plot one or two legend.
一个逻辑说明是否图一或两个传说。
参数：lgnd1
a numeric vector of two specify the position of the first legend box
两个指定一个数值向量的第一个图例“框中的位置
参数：lgnd2
a numeric vector of two specify the position of the second legend box, if OneLegend = FALSE
两个指定一个数值向量的第二个传说中的位置，如果OneLegend= FALSE
参数：arw1
a numeric vector of four numbers indicating start and end positions of the first arrows point to curves
一个数值向量四个数字，指示开始和结束位置的第一箭头指向曲线
参数：arw2
a numeric vector of four numbers indicating start and end positions of the second arrows point to curves
一个数值向量四个数字，指示开始和结束位置的所述第二箭头指向曲线
参数：...
other arguments of function plot
其他参数的函数plot
（作者）----------Author(s)----------
Zhong Guan <a href="mailto:zguan@iusb.edu">zguan@iusb.edu</a>
参考文献----------References----------
Guan, Z.(2001) Some Results About Empirical Likelihood Method, Ph.D. Thesis, The University of Toledo;
Guan, Z.(2004) A semiparametric change-point model, Biometrika, 91, 4, 849–862.
Guan, Z. Semiparametric Tests for Changepoints with Epidemic Alternatives.
参见----------See Also----------
schapt
schapt
实例----------Examples----------
require(sac) #load the package[加载包]
k<-30
n<-80
x<-rnorm(n,0,1)
x[(k+1):n]<-x[(k+1):n]+1.5
res<-SemiparChangePoint(x, alternative = "one.change")
Plot.ll(x, res$ll, col="blue")
## Nile data with one change-point: the annual flows drop in 1898 which corresponds [＃尼罗河数据于1898年，每年下降相对应的一个变化点：]
## to k=28. It is believed to be caused by the building of the first Aswan dam.[编号为k = 28。它被认为是造成由建筑物的第一阿斯旺水坝。]
if(! "package:sac" %in% search()) library(sac)
#if package sac has not been loaded, load it.[如果包囊尚未加载，加载它。]
if(! "package:stats" %in% search()) library(stats)
data(Nile)
plot(Nile, type="p")
Nile.res<-SemiparChangePoint(Nile, alternative = "one.change")
Color<-c(1,2,3,4); LTY<-c(1,2,3,4)
## Plots of estimated distribution functions[＃图的分布函数估计]
Graf.Diagnostic(Nile, Nile.res$k.hat, length(Nile), Nile.res$alpha.hat,
Nile.res$beta.hat, Color, LTY, xlab = "x", ylab = "Estimated DF's",
main="Model Diagnostic for Nile Data", OneLegend = FALSE, lgnd1 =
c(1100, 0.15), lgnd2 = c(600, .99), arw1=c(780, .93, 1010, .9),
arw2 = c(1165, .15, 1015, .24))
## Plot of loglikelihood function[号地loglikelihood功能的]
Plot.ll(Nile, Nile.res$ll, col = "blue")
Plot.ll(Nile, Nile.res$ll, col = "blue", xaxis.lab = seq(1871,1970, length = 100),
xlab = "Year")
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 2012-9-29 21:23:41
