# fitmarkov: Approximating a Markov chain In dave: Functions for "Data Analysis in Vegetation Ecology"

## 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

 ```1 2 3 4 5 6 7``` ```fitmarkov(veg, t, adjust = FALSE, ...) rfitmarkov(veg, t, adjust) ## Default S3 method: fitmarkov(veg, t, adjust = FALSE, ...) ## S3 method for class '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.

## Details

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

## 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'

## Note

The aim of this method is to provide a smooth curve based on input data. Because this relies on incomplete information, it is just one out of many solutions.

Otto Wildi

## 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

 ```1 2 3 4``` ```# 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) ```

dave documentation built on Nov. 17, 2017, 7:45 a.m.