dave (version 2.0)

fitmarkov: Approximating a Markov chain

Description

Given a vegetation data frame considerd a time series with releves as rows and species as columns transition matrices are derived vor each time step based on some simple assumptions. These are averaged and a model series is derived trough scalar products. Time steps are given in a separate vector t. Missing steps are properly processed.

Usage

fitmarkov(veg, t, adjust = FALSE, ...)
rfitmarkov(veg, t, adjust)
# S3 method for default
fitmarkov(veg, t, adjust = FALSE, ...)
# S3 method for fitmarkov
plot(x,...)

Arguments

veg

This is a vegetation data frame, releves are rows, species columns

t

The time step scale of length according with rows in x

x

An object of class "fitmarkov"

adjust

A logical vector adjusting the sum of species scores to 1.0. Default is adjust=FALSE

…

Vector colors of any length for line colors, vector widths for line widths. See example below.

Value

An output list of class "fitmarkov" with at least the following intems:

fitted.data

The fitted time series'

raw.data

The input time series'

transition.matrix

The mean transition matrix'

t.measured

The time steps upon input where time steps may be missing'

t.modeled

The time steps upon output, no missing steps'

Details

This method yields a possible solution for fitting a Markov series. The true process may be very different.

References

Orloci, L., Anand, M. & He, X. 1993. Markov chain: a realistic model for temporal coenosere? Biom. Praxim 33: 7-26.

Lippe, E., De Smitt, J.T. & Glenn-Lewin, D.C. 1985. Markov models and succession: a test from a heathland in the Netherlands. Journal of Ecology 73: 775-791.

Wildi, O. 2017. Data Analysis in Vegetation Ecology. 3rd ed. CABI, Oxfordshire, Boston.

Examples

# NOT RUN {
# data frame ltim is Lippe's data (see references)
# ltim just contains the time scale of the same
o.fm<- fitmarkov(lveg,ltim$Year)
plot(o.fm)
# }