I spend some time looking for an algorithm to find local extrema in a vector (time series). The solution I used is to “walk” through the vector by step larger than 1, in order to retain only one value even when the values are very noisy (see the picture at the end of the post).

It goes like this :

findpeaks <- function(vec,bw=1,x.coo=c(1:length(vec)))
{
pos.x.max <- NULL
pos.y.max <- NULL
pos.x.min <- NULL
pos.y.min <- NULL for(i in 1:(length(vec)-1)) { if((i+1+bw)>length(vec)){
sup.stop <- length(vec)}else{sup.stop <- i+1+bw
}
if((i-bw)<1){inf.stop <- 1}else{inf.stop <- i-bw}
subset.sup <- vec[(i+1):sup.stop]
subset.inf <- vec[inf.stop:(i-1)]
is.max <- sum(subset.inf > vec[i]) == 0
is.nomin <- sum(subset.sup > vec[i]) == 0
no.max <- sum(subset.inf > vec[i]) == length(subset.inf)
no.nomin <- sum(subset.sup > vec[i]) == length(subset.sup)
if(is.max & is.nomin){
pos.x.max <- c(pos.x.max,x.coo[i])
pos.y.max <- c(pos.y.max,vec[i])
}
if(no.max & no.nomin){
pos.x.min <- c(pos.x.min,x.coo[i])
pos.y.min <- c(pos.y.min,vec[i])
}
}
return(list(pos.x.max,pos.y.max,pos.x.min,pos.y.min))
}

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** [R] tricks**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...