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Median with missing values analysis

Source: R/median2.R
median2.Rd

Compute the sample median.

By default, median2() works like the standard median() unless one or more values are missing: median() always returns NA in this case, but median2() checks if the median can be determined nevertheless.

Usage

median2(
  x,
  na.rm = FALSE,
  na.rm.amount = 0,
  na.rm.from = c("start", "end", "random"),
  even = c("mean", "low", "high"),
  ...
)

# S3 method for default
median2(
  x,
  na.rm = FALSE,
  na.rm.amount = 0,
  na.rm.from = c("first", "last", "random"),
  even = c("mean", "low", "high"),
  ...
)

Arguments

x

Numeric or similar. Vector to search for its median.

na.rm

Logical. If set to TRUE, missing values are removed before computation proceeds. Default is FALSE.

na.rm.amount

Numeric. Alternative to na.rm that only removes a specified number of missing values. Default is 0.

na.rm.from

String. If na.rm.amount is used, from which position in x should missing values be removed? Options are "first", "last", and "random". Default is "first".

even

Character. What to do if x has an even length and contains no missing values (or they were removed). The default, "mean", averages the two central values, "low" returns the lower central value, and "high" returns the higher one.

...

Optional further arguments for methods. Not used in the default method.

Value

Length-1 vector of the same type as x. The only exception occurs if x is logical or integer and its length is even, in which case the return value is double.

The output is NA (of the same type as x) if and only if the median can't be determined because of missing values, or if there are no values.

Details

median2() is a generic function, so new methods can be defined for it. As with stats::median() from base R, the default method described here should work for most classes for which a median is a reasonable concept (e.g., "Date").

If a new method is necessary, please make sure it deals with missing values like the default method does. See Implementing the algorithm for further details.

Author

Lukas Jung, R Core Team

Examples

# If no values are missing,
# it works like `median()`:
median(1:4)
#> [1] 2.5
median2(1:4)
#> [1] 2.5
median(c(1:3, 100, 1000))
#> [1] 3
median2(c(1:3, 100, 1000))
#> [1] 3

# With some `NA`s, the median can
# sometimes still be determined...
median2(c(0, 1, 1, 1, NA))
#> [1] 1
median2(c(0, 0, NA, 0, 0, NA, NA))
#> [1] 0

# ...unless there are too many `NA`s...
median2(c(0, 1, 1, 1, NA, NA))
#> [1] NA

# ...or too many unique values:
median2(c(0, 1, 2, 3, NA))
#> [1] NA