在 R 中通过 hmisc 描述函数
Describe function by hmisc in R
这里有人知道什么是 "info" 给出下面的输出。
R代码:
> c<-c(1,2,3,4)
> describe(c)
c
n missing unique **Info** Mean .05 .10 .25 .50 .75
200 0 100 1 50.5 5.95 10.90 25.75 50.50 75.25
.90 .95
90.10 95.05
来自http://cran.r-project.org/web/packages/Hmisc/Hmisc.pdf#page=67:
For numeric variables, describe adds an item called Info which is a relative information measure using the relative efficiency of a proportional odds/Wilcoxon test on the variable relative to the same test on a variable that has no ties. Info is related to how continuous the variable is, and ties are less harmful the more untied values there are. The formula for Info is one minus the sum of the cubes of relative frequencies of values divided by one minus the square of the reciprocal of the sample size. The lowest information comes from a variable having only one unique values following by a highly skewed binary variable. Info is reported to two decimal places.
这里有人知道什么是 "info" 给出下面的输出。
R代码:
> c<-c(1,2,3,4)
> describe(c)
c
n missing unique **Info** Mean .05 .10 .25 .50 .75
200 0 100 1 50.5 5.95 10.90 25.75 50.50 75.25
.90 .95
90.10 95.05
来自http://cran.r-project.org/web/packages/Hmisc/Hmisc.pdf#page=67:
For numeric variables, describe adds an item called Info which is a relative information measure using the relative efficiency of a proportional odds/Wilcoxon test on the variable relative to the same test on a variable that has no ties. Info is related to how continuous the variable is, and ties are less harmful the more untied values there are. The formula for Info is one minus the sum of the cubes of relative frequencies of values divided by one minus the square of the reciprocal of the sample size. The lowest information comes from a variable having only one unique values following by a highly skewed binary variable. Info is reported to two decimal places.