fmean: Fast (Grouped, Weighted) Mean for Matrix-Like Objects

In collapse: Advanced and Fast Data Transformation

Fast (Grouped, Weighted) Mean for Matrix-Like Objects

Description

fmean is a generic function that computes the (column-wise) mean of x, (optionally) grouped by g and/or weighted by w. The TRA argument can further be used to transform x using its (grouped, weighted) mean.

Usage

fmean(x, ...)

## Default S3 method:
fmean(x, g = NULL, w = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
      use.g.names = TRUE, nthreads = .op[["nthreads"]], ...)

## S3 method for class 'matrix'
fmean(x, g = NULL, w = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
      use.g.names = TRUE, drop = TRUE, nthreads = .op[["nthreads"]], ...)

## S3 method for class 'data.frame'
fmean(x, g = NULL, w = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
      use.g.names = TRUE, drop = TRUE, nthreads = .op[["nthreads"]], ...)

## S3 method for class 'grouped_df'
fmean(x, w = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
      use.g.names = FALSE, keep.group_vars = TRUE,
      keep.w = TRUE, nthreads = .op[["nthreads"]], ...)

Arguments

x	a numeric vector, matrix, data frame or grouped data frame (class 'grouped_df').
g	a factor, GRP object, atomic vector (internally converted to factor) or a list of vectors / factors (internally converted to a GRP object) used to group x.
w	a numeric vector of (non-negative) weights, may contain missing values.
TRA	an integer or quoted operator indicating the transformation to perform: 0 - "NA" | 1 - "fill" | 2 - "replace" | 3 - "-" | 4 - "-+" | 5 - "/" | 6 - "%" | 7 - "+" | 8 - "*" | 9 - "%%" | 10 - "-%%". See TRA.
na.rm	logical. Skip missing values in x. Defaults to TRUE and implemented at very little computational cost. If na.rm = FALSE a NA is returned when encountered.
use.g.names	logical. Make group-names and add to the result as names (default method) or row-names (matrix and data frame methods). No row-names are generated for data.table's.
nthreads	integer. The number of threads to utilize. See Details of fsum.
drop	matrix and data.frame method: Logical. TRUE drops dimensions and returns an atomic vector if g = NULL and TRA = NULL.
keep.group_vars	grouped_df method: Logical. FALSE removes grouping variables after computation.
keep.w	grouped_df method: Logical. Retain summed weighting variable after computation (if contained in grouped_df).
...	arguments to be passed to or from other methods. If TRA is used, passing set = TRUE will transform data by reference and return the result invisibly.

Details

The weighted mean is computed as sum(x * w) / sum(w), using a single pass in C. If na.rm = TRUE, missing values will be removed from both x and w i.e. utilizing only x[complete.cases(x,w)] and w[complete.cases(x,w)].

For further computational details see fsum, which works equivalently.

Value

The (w weighted) mean of x, grouped by g, or (if TRA is used) x transformed by its (grouped, weighted) mean.

See Also

fmedian, fmode, Fast Statistical Functions, Collapse Overview

Examples

## default vector method
mpg <- mtcars$mpg
fmean(mpg)                         # Simple mean
fmean(mpg, w = mtcars$hp)          # Weighted mean: Weighted by hp
fmean(mpg, TRA = "-")              # Simple transformation: demeaning (See also ?W)
fmean(mpg, mtcars$cyl)             # Grouped mean
fmean(mpg, mtcars[8:9])            # another grouped mean.
g <- GRP(mtcars[c(2,8:9)])
fmean(mpg, g)                      # Pre-computing groups speeds up the computation
fmean(mpg, g, mtcars$hp)           # Grouped weighted mean
fmean(mpg, g, TRA = "-")           # Demeaning by group
fmean(mpg, g, mtcars$hp, "-")      # Group-demeaning using weighted group means

## data.frame method
fmean(mtcars)
fmean(mtcars, g)
fmean(fgroup_by(mtcars, cyl, vs, am))  # Another way of doing it..
head(fmean(mtcars, g, TRA = "-"))      # etc..

## matrix method
m <- qM(mtcars)
fmean(m)
fmean(m, g)
head(fmean(m, g, TRA = "-")) # etc..
 
## method for grouped data frames - created with dplyr::group_by or fgroup_by
library(dplyr)
mtcars %>% group_by(cyl,vs,am) %>% fmean()         # Ordinary
mtcars %>% group_by(cyl,vs,am) %>% fmean(hp)       # Weighted
mtcars %>% group_by(cyl,vs,am) %>% fmean(hp, "-")  # Weighted Transform
mtcars %>% group_by(cyl,vs,am) %>%
           select(mpg,hp) %>% fmean(hp, "-")      # Only mpg

mtcars %>% fgroup_by(cyl,vs,am) %>%                # Equivalent and faster !
           fselect(mpg,hp) %>% fmean(hp, "-")

collapse documentation built on Nov. 13, 2023, 1:08 a.m.