statByIndex: Computes statistics by index or by row

In plw: Probe level Locally moderated Weighted t-tests.

Description

These function give the same result as by(x,index,mad) by(x,index,mean) by(x,index,median) but are much faster. NOTE: The index vector is assumed to be SORTED and should contain INTEGER values only.

The function meanSdByRow computes mean and standard deviation for each row of the matrix mat. A list with mean and sd is returned and gives the the same result as:

list(mean=apply(mat,1,mean),sd=apply(mat,1,sd))

Usage

madByIndex(x,index)
meanByIndex(x,index)
medianByIndex(x,index)
orderStatByIndex(x,index,orderStat)
sdByIndex(x,index)
meanSdByRow(mat)

Arguments

x	Data vector
index	Index vector
orderStat	Which order statistic to compute
mat	Matrix

Details

See the definition (R-code) of each function for details.

Value

All but the last function: A vector with the statistic for each level if index. meanSdByRow: A list with items mean and sd.

Author(s)

Magnus Astrand

See Also

by, apply

Examples

## Example 1
## Computing, mad, mean and median by index.
## Compares with the result obtained using by(...) 

n<-10000
x<-rnorm(n)
index<-sort(round(runif(n,0.5,10.5)))

mad1<-madByIndex(x,index)
mad2<-by(x,index,mad)

mean1<-meanByIndex(x,index)
mean2<-by(x,index,mean)

median1<-medianByIndex(x,index)
median2<-by(x,index,median)

par(mfrow=c(2,2),mar=c(4,4,1.5,.5),mgp=c(1.5,.25, 0))
plot(mad1,mad2,main="Comparing mad",pch=19)
abline(a=0,b=1,col=2)
plot(mean1,mean2,main="Comparing mean",pch=19)
abline(a=0,b=1,col=2)
plot(median1,median2,main="Comparing median",pch=19)
abline(a=0,b=1,col=2)


## Example 2
## Computing, median by index
## Compares with the running time when using by(...)
n<-200000
x<-rnorm(n)
index<-sort(round(runif(n,0.5,10.5)))

system.time(median1<-medianByIndex(x,index))

system.time(median2<-by(x,index,median))


## Example 3
## Computing, mean and sd by row 
## Compares with using apply
nrow<-5000
ncol<-20
mat<-matrix(rnorm(ncol*nrow),nrow,ncol)

system.time(res1<-meanSdByRow(mat))
system.time(res2<-list(mean=apply(mat,1,mean),sd=apply(mat,1,sd)))

par(mfrow=c(1,2),mar=c(4,4,1.5,.5),mgp=c(1.5,.25, 0))
plot(res1$mean,res2$mean,pch='.')
plot(res1$sd,res2$sd,pch='.')

plw documentation built on April 28, 2020, 6:38 p.m.