Source: golang-github-vividcortex-ewma
Section: devel
Priority: extra
Maintainer: Debian Go Packaging Team
Uploaders: Dr. Tobias Quathamer
Build-Depends: debhelper (>= 10),
dh-golang,
golang-any
Standards-Version: 3.9.8
Homepage: https://github.com/vividcortex/ewma
Vcs-Browser: https://anonscm.debian.org/cgit/pkg-go/packages/golang-github-vividcortex-ewma.git
Vcs-Git: https://anonscm.debian.org/git/pkg-go/packages/golang-github-vividcortex-ewma.git
XS-Go-Import-Path: github.com/VividCortex/ewma
Package: golang-github-vividcortex-ewma-dev
Architecture: all
Depends: ${shlibs:Depends},
${misc:Depends}
Description: Exponentially Weighted Moving Average algorithms for Go
An exponentially weighted moving average is a way to continuously
compute a type of average for a series of numbers, as the numbers
arrive. After a value in the series is added to the average, its
weight in the average decreases exponentially over time. This biases
the average towards more recent data. EWMAs are useful for several
reasons, chiefly their inexpensive computational and memory cost, as
well as the fact that they represent the recent central tendency of
the series of values.