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diffusion

The R package diffusion is for forecasting with diffusion curves.

Currently the following diffusion models are implemented:

  1. Bass model
  2. Gompertz model
  3. Gamma/Shifted Gompertz model
  4. Weibull model
  5. Norton-Bass model for generational modelling (not working well)

Installation

Stable version can be installed from CRAN:

install.packages("diffusion")

For installation from github use remotes:

if (!require("remotes")){install.packages("remotes")}
remotes::install_github("mamut86/diffusion")

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Version

Install

install.packages('diffusion')

Monthly Downloads

431

Version

0.4.0

License

LGPL-2.1

Issues

Pull Requests

Stars

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Maintainer

Oliver Schaer

Last Published

April 16th, 2024

Functions in diffusion (0.4.0)

tsMetal

Time series: U.S. Merchant Marine conversion to metal
tsCovid

Time series: COVID-19 confirmed cases US
plot.diffusion

Plot a fitted diffusion curve.
diffusion

Fit various diffusion curves.
difcurve

Calculates the values for various diffusion curves, given some parameters.
is.diffusion

Diffusion class checkers
print.diffusion

Print a fitted diffusion curve.
predict.diffusion

Predict future periods of a fitted diffusion curve.
tsSafari

Time series: Safari Browser market share
Nortonbass_error

Fits Norton Bass curve and estimated RMSE
plot.seqdiffusion

Plot sequentially fitted diffusion curves.
Nortonbass

Norton-Bass model
print.seqdiffusion

Print sequentially fitted diffusion curves.
Nortonbass_startvalgen

Fits Norton Bass curve and estimated RMSE
seqdiffusion

Enables fitting various sequential diffusion curves.
tsIbm

Time series: Sales of IBM Computers
tsAc

Time series: Assassins Creeds
tsChicken

Time series: Chicken weight
tsCarstock

Time series: Stock of cars
tsWindows

Time series: Windows OS Platform Statistics