Plot function for an RLum.Results S4 class object

Description

The function provides a standardised plot output for data of an RLum.Results S4 class object

Usage

plot_RLum.Results(object, single = TRUE, ...)

Arguments

Details

The function produces a multiple plot output. A file output is recommended (e.g., pdf).

Value

Returns multiple plots.

Function version

0.2.1 (2016-05-16 22:24:15)

Note

Not all arguments available for plot will be passed! Only plotting of RLum.Results objects are supported.

Author(s)

Christoph Burow, University of Cologne (Germany), Sebastian Kreutzer, IRAMAT-CRP2A, Universite Bordeaux Montaigne (France)
R Luminescence Package Team

References

#

See Also

plot, plot_RLum,

Examples

###load data
data(ExampleData.DeValues, envir = environment())

# apply the un-logged minimum age model
mam <- calc_MinDose(data = ExampleData.DeValues$CA1, sigmab = 0.2, log = TRUE, plot = FALSE)

##plot
plot_RLum.Results(mam)

# estimate the number of grains on an aliquot
grains<- calc_AliquotSize(grain.size = c(100,150), sample.diameter = 1, plot = FALSE, MC.iter = 100)

##plot
plot_RLum.Results(grains)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(Luminescence)
Welcome to the R package Luminescence version 0.6.0 [Built: 2016-05-30 16:47:30 UTC]
A common luminescence reader customer: 'If anything can go wrong, it will.'
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Luminescence/plot_RLum.Results.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot_RLum.Results
> ### Title: Plot function for an RLum.Results S4 class object
> ### Aliases: plot_RLum.Results
> ### Keywords: aplot
> 
> ### ** Examples
> 
> 
> 
> ###load data
> data(ExampleData.DeValues, envir = environment())
> 
> # apply the un-logged minimum age model
> mam <- calc_MinDose(data = ExampleData.DeValues$CA1, sigmab = 0.2, log = TRUE, plot = FALSE)

----------- meta data -----------
  n par sigmab logged      Lmax      BIC
 62   3    0.2   TRUE -32.43138 84.14389

--- final parameter estimates ---
 gamma sigma   p0 mu
  3.82  0.44 0.02  0

------ confidence intervals -----
      2.5 % 97.5 %
gamma  3.65   3.98
sigma  0.29   0.64
p0       NA   0.28

------ De (asymmetric error) -----
    De lower upper
 45.64 38.61 53.65

------ De (symmetric error) -----
    De error
 45.64  3.84
> 
> ##plot
> plot_RLum.Results(mam)
> 
> # estimate the number of grains on an aliquot
> grains<- calc_AliquotSize(grain.size = c(100,150), sample.diameter = 1, plot = FALSE, MC.iter = 100)

 [calc_AliquotSize]

 ---------------------------------------------------------
 mean grain size (microns)  : 125
 sample diameter (mm)       : 1
 packing density            : 0.65
 number of grains           : 42

 --------------- Monte Carlo Estimates -------------------
 number of iterations (n)     : 100
 median                       : 43
 mean                         : 45
 standard deviation (mean)    : 21
 standard error (mean)        : 2.1
 95% CI from t-test (mean)    : 41 - 49
 standard error from CI (mean): 2.1
 ---------------------------------------------------------
> 
> ##plot
> plot_RLum.Results(grains)
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>