对ts作图时，在x轴上显示详细时间点,用mean计算截断均值,向量自回归(VAR)模型,指数分布的QQ图,_x<-ts(a1)

http://blog.csdn.net/liu7788414/article/details/44488215

对ts作图时，在x轴上显示详细时间点

x<-ts(1:30,start=c(1900,1),frequency=4)
plot(x,type='l')
axis(1, at = c(1900, 1901, 1902, 1903,1904,1905,1906),labels = expression(1900, 1901, 1902, 1903, 1904,1905,1906))
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plot(x)
axis(1, at=1900:1907)
axis(1, at=seq(1900, 1908, by=1/4), labels=FALSE, tcl=-1/4)
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用mean计算截断均值

x <- c(0:10, 50)
xm <- mean(x)
mean(x, trim = 0.10)
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trim就是截断，表示去掉最高和最低的10%。

做向量自回归(VAR)模型

用vars和urca包。

调用Matlab

install.packages("R.matlab")
library(R.matlab)
path <- system.file("mat-files", package="R.matlab")
mat <- readMat(file.path(path, "structLooped.mat"))
s <- mat$s
fields <- dimnames(s)[[1]]
cat("Field names: ", paste(fields, collapse=", "), "\n", sep="");
print(s)
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指数分布的QQ图

install.packages("qualityTools")

library(qualityTools)

x= rexp(100)

qqPlot(x,"exponential")
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