# plot_Histogram

##### Plot a histogram with separate error plot

Function plots a predefined histogram with an accompanying error plot as suggested by Rex Galbraith at the UK LED in Oxford 2010.

##### Usage

```
plot_Histogram(data, na.rm = TRUE, mtext, cex.global, se, rug,
normal_curve, summary, summary.pos, colour, interactive = FALSE, ...)
```

##### Arguments

- data
data.frame or '>RLum.Results object (

**required**): for`data.frame`

: two columns: De (`data[,1]`

) and De error (`data[,2]`

)- na.rm
logical (

*with default*): excludes`NA`

values from the data set prior to any further operations.- mtext
- cex.global
numeric (

*with default*): global scaling factor.- se
logical (

*optional*): plots standard error points over the histogram, default is`FALSE`

.- rug
logical (

*optional*): adds rugs to the histogram, default is`TRUE`

.- normal_curve
logical (

*with default*): adds a normal curve to the histogram. Mean and sd are calculated from the input data. More see details section.- summary
character (

*optional*): add statistic measures of centrality and dispersion to the plot. Can be one or more of several keywords. See details for available keywords.- summary.pos
numeric or character (

*with default*): optional position coordinates or keyword (e.g.`"topright"`

) for the statistical summary. Alternatively, the keyword`"sub"`

may be specified to place the summary below the plot header. However, this latter option in only possible if`mtext`

is not used. In case of coordinate specification, y-coordinate refers to the right y-axis.- colour
numeric or character (

*with default*): optional vector of length 4 which specifies the colours of the following plot items in exactly this order: histogram bars, rug lines, normal distribution curve and standard error points (e.g.,`c("grey", "black", "red", "grey")`

).- interactive
logical (

*with default*): create an interactive histogram plot (requires the 'plotly' package)- ...
further arguments and graphical parameters passed to plot or hist. If y-axis labels are provided, these must be specified as a vector of length 2 since the plot features two axes (e.g.

`ylab = c("axis label 1", "axis label 2")`

). Y-axes limits (`ylim`

) must be provided as vector of length four, with the first two elements specifying the left axes limits and the latter two elements giving the right axis limits.

##### Details

If the normal curve is added, the y-axis in the histogram will show the probability density.

A statistic summary, i.e. a collection of statistic measures of centrality and dispersion (and further measures) can be added by specifying one or more of the following keywords:

`"n"`

(number of samples),`"mean"`

(mean De value),`"mean.weighted"`

(error-weighted mean),`"median"`

(median of the De values),`"sdrel"`

(relative standard deviation in percent),`"sdrel.weighted"`

(error-weighted relative standard deviation in percent),`"sdabs"`

(absolute standard deviation),`"sdabs.weighted"`

(error-weighted absolute standard deviation),`"serel"`

(relative standard error),`"serel.weighted"`

(error-weighted relative standard error),`"seabs"`

(absolute standard error),`"seabs.weighted"`

(error-weighted absolute standard error),`"kurtosis"`

(kurtosis) and`"skewness"`

(skewness).

##### Note

The input data is not restricted to a special type.

##### Function version

0.4.4 (2018-01-21 17:22:38)

##### How to cite

Dietze, M., Kreutzer, S. (2018). plot_Histogram(): Plot a histogram with separate error plot. Function version 0.4.4. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J. (2018). Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.8.6. https://CRAN.R-project.org/package=Luminescence

##### See Also

##### Examples

```
# NOT RUN {
## load data
data(ExampleData.DeValues, envir = environment())
ExampleData.DeValues <-
Second2Gray(ExampleData.DeValues$BT998, dose.rate = c(0.0438,0.0019))
## plot histogram the easiest way
plot_Histogram(ExampleData.DeValues)
## plot histogram with some more modifications
plot_Histogram(ExampleData.DeValues,
rug = TRUE,
normal_curve = TRUE,
cex.global = 0.9,
pch = 2,
colour = c("grey", "black", "blue", "green"),
summary = c("n", "mean", "sdrel"),
summary.pos = "topleft",
main = "Histogram of De-values",
mtext = "Example data set",
ylab = c(expression(paste(D[e], " distribution")),
"Standard error"),
xlim = c(100, 250),
ylim = c(0, 0.1, 5, 20))
# }
```

*Documentation reproduced from package Luminescence, version 0.8.6, License: GPL-3*