dby: Calculate summary statistics grouped by

In mets: Analysis of Multivariate Event Times

Calculate summary statistics grouped by

Description

Calculate summary statistics grouped by variable

Usage

dby(
  data,
  INPUT,
  ...,
  ID = NULL,
  ORDER = NULL,
  SUBSET = NULL,
  SORT = 0,
  COMBINE = !REDUCE,
  NOCHECK = FALSE,
  ARGS = NULL,
  NAMES,
  COLUMN = FALSE,
  REDUCE = FALSE,
  REGEX = mets.options()$regex,
  ALL = TRUE
)

Arguments

data	Data.frame
INPUT	Input variables (character or formula)
...	functions
ID	id variable
ORDER	(optional) order variable
SUBSET	(optional) subset expression
SORT	sort order (id+order variable)
COMBINE	If TRUE result is appended to data
NOCHECK	No sorting or check for missing data
ARGS	Optional list of arguments to functions (...)
NAMES	Optional vector of column names
COLUMN	If TRUE do the calculations for each column
REDUCE	Reduce number of redundant rows
REGEX	Allow regular expressions
ALL	if FALSE only the subset will be returned

Details

Calculate summary statistics grouped by

dby2 for column-wise calculations

Author(s)

Klaus K. Holst and Thomas Scheike

Examples

n <- 4
k <- c(3,rbinom(n-1,3,0.5)+1)
N <- sum(k)
d <- data.frame(y=rnorm(N),x=rnorm(N),id=rep(seq(n),k),num=unlist(sapply(k,seq)))
d2 <- d[sample(nrow(d)),]

dby(d2, y~id, mean)
dby(d2, y~id + order(num), cumsum)

dby(d,y ~ id + order(num), dlag)
dby(d,y ~ id + order(num), dlag, ARGS=list(k=1:2))
dby(d,y ~ id + order(num), dlag, ARGS=list(k=1:2), NAMES=c("l1","l2"))

dby(d, y~id + order(num), mean=mean, csum=cumsum, n=length)
dby(d2, y~id + order(num), a=cumsum, b=mean, N=length, l1=function(x) c(NA,x)[-length(x)])

dby(d, y~id + order(num), nn=seq_along, n=length)
dby(d, y~id + order(num), nn=seq_along, n=length)

d <- d[,1:4]
dby(d, x<0) <- list(z=mean)
d <- dby(d, is.na(z), z=1)

f <- function(x) apply(x,1,min)
dby(d, y+x~id, min=f)

dby(d,y+x~id+order(num), function(x) x)

f <- function(x) { cbind(cumsum(x[,1]),cumsum(x[,2]))/sum(x)}
dby(d, y+x~id, f)

## column-wise
a <- d
dby2(a, mean, median, REGEX=TRUE) <- '^[y|x]'~id
a
## wildcards 
dby2(a,'y*'+'x*'~id,mean) 


## subset
dby(d, x<0) <- list(z=NA)
d
dby(d, y~id|x>-1, v=mean,z=1)
dby(d, y+x~id|x>-1, mean, median, COLUMN=TRUE)

dby2(d, y+x~id|x>0, mean, REDUCE=TRUE)

dby(d,y~id|x<0,mean,ALL=FALSE)

a <- iris
a <- dby(a,y=1)
dby(a,Species=="versicolor") <- list(y=2)

mets documentation built on May 29, 2024, 3:51 a.m.