Fast (Grouped, Weighted) Mean for Matrix-Like Objects
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.
fmean(x, ...)
## Default S3 method:
fmean(x, g = NULL, w = NULL, TRA = NULL, na.rm = TRUE,
use.g.names = TRUE, ...)
## S3 method for class 'matrix'
fmean(x, g = NULL, w = NULL, TRA = NULL, na.rm = TRUE,
use.g.names = TRUE, drop = TRUE, ...)
## S3 method for class 'data.frame'
fmean(x, g = NULL, w = NULL, TRA = NULL, na.rm = TRUE,
use.g.names = TRUE, drop = TRUE, ...)
## S3 method for class 'grouped_df'
fmean(x, w = NULL, TRA = NULL, na.rm = TRUE,
use.g.names = FALSE, keep.group_vars = TRUE, keep.w = TRUE, ...)x |
a numeric vector, matrix, data frame or grouped data frame (class 'grouped_df'). |
g |
a factor, |
w |
a numeric vector of (non-negative) weights, may contain missing values. |
TRA |
an integer or quoted operator indicating the transformation to perform:
1 - "replace_fill" | 2 - "replace" | 3 - "-" | 4 - "-+" | 5 - "/" | 6 - "%" | 7 - "+" | 8 - "*" | 9 - "%%" | 10 - "-%%". See |
na.rm |
logical. Skip missing values in |
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. |
drop |
matrix and data.frame method: Logical. |
keep.group_vars |
grouped_df method: Logical. |
keep.w |
grouped_df method: Logical. Retain summed weighting variable after computation (if contained in |
... |
arguments to be passed to or from other methods. |
Missing-value removal as controlled by the na.rm argument is done very efficiently by simply skipping them in the computation (thus setting na.rm = FALSE on data with no missing values doesn't give extra speed). Large performance gains can nevertheless be achieved in the presence of missing values if na.rm = FALSE, since then the corresponding computation is terminated once a NA is encountered and NA is returned (unlike mean which just runs through without any checks).
The weighted mean is computed as sum(x * w) / sum(w). 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)].
This all seamlessly generalizes to grouped computations, which are performed in a single pass (without splitting the data) and therefore extremely fast.
When applied to data frames with groups or drop = FALSE, fmean preserves all column attributes (such as variable labels) but does not distinguish between classed and unclassed object (thus applying fmean to a factor column will give a 'malformed factor' error). The attributes of the data frame itself are also preserved.
The (w weighted) mean of x, grouped by g, or (if TRA is used) x transformed by its mean, grouped by g.
## 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, "-")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.