abc: ABC analysis

In tsutils: Time Series Exploration, Modelling and Forecasting

ABC analysis

Description

Perform ABC analysis on a set of time series.

Usage

abc(x, prc = c(0.2, 0.3, 0.5))

## S3 method for class 'abc'
plot(x, cex.prc = 0.8, ...)

Arguments

x	this can either be an array, where each column is a series, or a vector of values. If x is an array of time series, then the importance of each series is calculated as the mean of the observations (sales volume). Otherwise, value can be whatever quantity is provided.
prc	a vector of percentages indicating how many items are included in each class. By default this is c(0.2,0.3,0.5), but any set of percentage values can be used as long as 0<=prc[i]<=1 and sum(prc)==1.
cex.prc	font size of percentages reported in plot.
...	additional arguments passed to the plot.

Value

Return object of class abc and contains:

• value: a vector containing the importance value of each series.

• class: a vector containing the class membership of each series.

• rank: a vector containing the rank of each series, with 1 being the highest ranking series.

• conc: the importance concentration of each class, as percentage of total value.

Methods (by generic)

• plot(abc): plot ABC or XYZ analyses.

Author(s)

Nikolaos Kourentzes, [e-mail].

References

Ord K., Fildes R., Kourentzes N. (2017) Principles of Business Forecasting, 2e. Wessex Press Publishing Co., p.515-518.

See Also

xyz, abcxyz.

Examples

x <- abs(matrix(cumsum(rnorm(5400,0,1)),36,150))
z <- abc(x)
print(z)
plot(z)

tsutils documentation built on Nov. 15, 2023, 1:08 a.m.