# calc_Statistics: Function to calculate statistic measures In R-Lum/Luminescence: Comprehensive Luminescence Dating Data Analysis

## Description

This function calculates a number of descriptive statistics for estimates with a given standard error (SE), most fundamentally using error-weighted approaches.

## Usage

 ```1 2 3 4 5 6 7``` ```calc_Statistics( data, weight.calc = "square", digits = NULL, n.MCM = NULL, na.rm = TRUE ) ```

## Arguments

 `data` data.frame or RLum.Results object (required): for data.frame two columns: De (`data[,1]`) and De error (`data[,2]`). To plot several data sets in one plot the data sets must be provided as `list`, e.g. `list(data.1, data.2)`. `weight.calc` character: type of weight calculation. One out of `"reciprocal"` (weight is 1/error), `"square"` (weight is 1/error^2). Default is `"square"`. `digits` integer (with default): round numbers to the specified digits. If digits is set to `NULL` nothing is rounded. `n.MCM` numeric (with default): number of samples drawn for Monte Carlo-based statistics. `NULL` (the default) disables MC runs. `na.rm` logical (with default): indicating whether `NA` values should be stripped before the computation proceeds.

## Details

The option to use Monte Carlo Methods (`n.MCM`) allows calculating all descriptive statistics based on random values. The distribution of these random values is based on the Normal distribution with `De` values as means and `De_error` values as one standard deviation. Increasing the number of MCM-samples linearly increases computation time. On a Lenovo X230 machine evaluation of 25 Aliquots with n.MCM = 1000 takes 0.01 s, with n = 100000, ca. 1.65 s. It might be useful to work with logarithms of these values. See Dietze et al. (2016, Quaternary Geochronology) and the function plot_AbanicoPlot for details.

## Value

Returns a list with weighted and unweighted statistic measures.

0.1.7

## How to cite

Dietze, M., 2020. calc_Statistics(): Function to calculate statistic measures. Function version 0.1.7. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., 2020. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.7. https://CRAN.R-project.org/package=Luminescence

## Author(s)

Michael Dietze, GFZ Potsdam (Germany) , RLum Developer Team

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```## load example data data(ExampleData.DeValues, envir = environment()) ## show a rough plot of the data to illustrate the non-normal distribution plot_KDE(ExampleData.DeValues\$BT998) ## calculate statistics and show output str(calc_Statistics(ExampleData.DeValues\$BT998)) ## Not run: ## now the same for 10000 normal distributed random numbers with equal errors x <- as.data.frame(cbind(rnorm(n = 10^5, mean = 0, sd = 1), rep(0.001, 10^5))) ## note the congruent results for weighted and unweighted measures str(calc_Statistics(x)) ## End(Not run) ```

R-Lum/Luminescence documentation built on Jan. 4, 2020, 10:44 p.m.