Bclim (version 2.3.1)

BclimMixSer: Serial version of Bclim mixture analysis

Description

Function to approximate marginal data posteriors as mixtures of Gaussians

Usage

BclimMixSer(MDP, G = 10, mixwarnings = FALSE)

Arguments

MDP

A set of marginal data posteriors, as produced by BclimLayer

G

The number of Gaussian groups required for each layer to be partitioned into. The default of 10 is usually fine.

mixwarnings

Whether to suppress mixture warnings (default) or not.

Value

• Outputs a list containing the following objects:
• MDP
  A nsamples x n x m array (these values are described below)
• n
  The number of layers
• m
  The number of climate dimensions (always 3)
• n.samp
  The number of samples given in BclimLayer
• ScMean
  The raw climate means (used for standardisation purposes)
• ScVar
  The raw climate variances (used for standardisation purposes)
• G
  The number of mixture groups (as above)
• mu.mat
  An estimate of the Gaussian mixture mean components
• tau.mat
  An estimate of the Gaussian mixture precision components
• p.mat
  An estimate of the Gaussian mixture proportions

Details

This function approximates marginal data posteriors (MDPs) as mixtures of Gaussians. The mixture algorithm is taken from the Mclust package which is a required installation for this to run. This is the serial version, i.e. it only uses one processor, as opposed to the BclimMixPar parallel version which will run much faster but requires extra packages to be installed and a multi-core machine.

References

See Arxiv paper at http://arxiv.org/abs/1206.5009.

See Also

The output here can be used as an input to BclimMCMC. See the main BclimRun function for more details of the other stages you might need to run.

Examples

# Set the working directory using setwd (not shown)

# Download and load in the response surfaces:
url1 <- 'http://mathsci.ucd.ie/~parnell_a/required.data3D.RData'
download.file(url1,'required_data3D.RData')

# and now the pollen
url2 <- 'http://mathsci.ucd.ie/~parnell_a/SlugganPollen.txt'
download.file(url2,'SlugganPollen.txt')

# and finally the chronologies
url3 <- 'http://mathsci.ucd.ie/~parnell_a/Sluggan_2chrons.txt'
download.file(url3,'Slugganchrons.txt')

# Create variables which state the locations of the pollen and chronologies
pollen.loc <- paste(getwd(),'/SlugganPollen.txt',sep='')
chron.loc <- paste(getwd(),'/Slugganchrons.txt',sep='')

# Load in the response surfaces
load('required.data3D.RData')

## note that all of these functions have further options you can change with
step1 <- BclimLayer(pollen.loc,required.data3D=required.data3D)
step2 <- BclimMixSer(step1) 
# See also the parallelised version BclimMixPar if you have doMC and foreach installed
step3 <- BclimMCMC(step2,chron.loc) 
# You should probably do some convergence checking after this step
step4 <- BclimInterp(step2,step3) 
results <- BclimCompile(step1,step2,step3,step4,core.name="Sluggan Moss")

# Create a plot of MTCO (dim=2)
plotBclim(results,dim=2)

# Create a volatility plot
plotBclimVol(results,dim=2)