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mosaic (version 0.5-1)

mean: Aggregating summary statistics

Description

These drop-in replacements and new summary statistics functions are formula-aware and allow the use of simple names within data frames. When given formulas, they call aggregate using the formula.

Usage

mean(x, ..., na.rm=FALSE, trim=0)
  ## S3 method for class 'ANY':
mean(x, ..., na.rm=FALSE, trim=0)
  ## S3 method for class 'numeric':
mean(x, ..., na.rm=FALSE, trim=0)
  ## S3 method for class 'data.frame':
mean(x, ..., na.rm=TRUE, trim=0)
  ## S3 method for class 'formula':
mean(x, data=parent.frame(), ...,
    na.rm=TRUE, trim=0)
  median(x, ..., na.rm=FALSE)
  ## S3 method for class 'ANY':
median(x, ..., na.rm=FALSE)
  ## S3 method for class 'numeric':
median(x, ..., na.rm=FALSE)
  ## S3 method for class 'numeric':
median(x, ..., na.rm=FALSE)
  ## S3 method for class 'formula':
median(x, data=parent.frame(), ...,
    na.rm=TRUE)
  sd(x, ..., na.rm=FALSE)
  ## S3 method for class 'ANY':
sd(x, ..., na.rm=FALSE)
  ## S3 method for class 'numeric':
sd(x, ..., na.rm=FALSE)
  ## S3 method for class 'data.frame':
sd(x, ..., na.rm=TRUE)
  ## S3 method for class 'formula':
sd(x, data=parent.frame(), ...,
    na.rm=TRUE)
  var(x, y=NULL, na.rm=FALSE, use='everything', data=NULL)
  ## S3 method for class 'ANY,ANY,ANY,ANY,ANY':
var(x, y, na.rm=FALSE,
    use='everything', data=parent.frame())
  ## S3 method for class 'numeric,numeric,ANY,ANY,ANY':
var(x, y,
    na.rm=FALSE, use='everything', data=parent.frame())
  ## S3 method for class 'numeric,ANY,ANY,ANY,ANY':
var(x, y=NULL,
    na.rm=FALSE, use='everything', data=parent.frame())
  ## S3 method for class 'matrix,ANY,ANY,ANY,ANY':
var(x, y, na.rm=FALSE,
    use='everything', data=parent.frame())
  ## S3 method for class 'data.frame,ANY,ANY,ANY,ANY':
var(x, y,
    na.rm=TRUE, use='everything')
  ## S3 method for class 'formula,missing,ANY,ANY,missing':
var(x, y,
    na.rm=TRUE, use='everything', data=parent.frame())
  ## S3 method for class 'formula,missing,ANY,ANY,data.frame':
var(x, y,
    na.rm=TRUE, use='everything', data=parent.frame())
  ## S3 method for class 'formula,data.frame,ANY,ANY,missing':
var(x,
    y=parent.frame(), na.rm=FALSE, use='everything')
  ## S3 method for class 'ANY,missing,ANY,ANY,data.frame':
var(x,
    y = NULL, na.rm = FALSE, use = "everything",
    data = parent.frame())
  ## S3 method for class 'ANY,ANY,ANY,ANY,data.frame':
var(x, y = NULL,
    na.rm = FALSE, use = "everything",
    data = parent.frame())
  min(x, ..., na.rm = FALSE)
  max(x, ..., na.rm = FALSE)

Arguments

x
a vector
na.rm
logical indicating whether NAs should be removed before calculating
...
additional arguments
trim
a numeric indicating the proportion to be trimmed from each tail before calculating mean
data
a data frame
y
second vector allows for computation of covariances
use
passed along to base::var

Details

These methods are wrappers around functions and methods in the base and stats packages and provide additional interfaces.

The default value for na.rm is reversed from the functions in base and stats. Also, na.rm, use, and trim follow ... so must be named using their full names.

See Also

aggregate, sd, var, median, mean, max, min, sum

Examples

Run this code
data(HELPrct)
mean(age, data=HELPrct)
mean(~age, data=HELPrct)
mean(age ~ 1, data=HELPrct)
mean(age ~ NULL, data=HELPrct)
mean(HELPrct$age)
mean(age ~ sex, data=HELPrct)
mean(age ~ sex & treat, data=HELPrct)
median(age, data=HELPrct)
median(~age, data=HELPrct)
median(age ~ 1, data=HELPrct)
median(age ~ NULL, data=HELPrct)
median(HELPrct$age)
median(age ~ sex, data=HELPrct)
median(age ~ sex & treat, data=HELPrct)
sd(age, data=HELPrct)
sd(~age, data=HELPrct)
sd(age ~ 1, data=HELPrct)
sd(age ~ NULL, data=HELPrct)
sd(HELPrct$age)
sd(age ~ sex, data=HELPrct)
sd(age ~ sex & treat, data=HELPrct)
var(age, data=HELPrct)
var(~age, data=HELPrct)
var(age ~ 1, data=HELPrct)
var(age ~ NULL, data=HELPrct)
var(HELPrct$age)
var(age ~ sex, data=HELPrct)
var(age ~ sex & treat, data=HELPrct)
min(age, data=HELPrct)
max(age, data=HELPrct)
max(~age, data=HELPrct)
max(age ~ 1, data=HELPrct)
max(age ~ NULL, data=HELPrct)
max(HELPrct$age)
max(age ~ sex, data=HELPrct)
max(age ~ sex & treat, data=HELPrct)

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