elementR_standard: Object elementR_standard
In elementR: An Framework for Reducing Elemental LAICPMS Data from Solid Structures

Description Usage Format Details Inheritance Fields Methods See Also Examples

The R6Class object elementR_standard contains the main information needed for the filtration of a single standard replicate.

1	elementR_standard

An R6Class generator object

As a subclass object, the elementR_standard object already contains all fields and methods from the elementR_data. Moreover, it also contains items specifically designed for standard filtration.

The elementR_standard object inherits from the elementR_data.

type: A character string indicating the type of replicate (here, "standard")

dataOutlierFree: A matrix corresponding to the dataNorm without abnomalities

data_standFinalMean: A vector corresponding to the average of dataOutlierFree per chemical element

data_standFinalSD: A vector corresponding to the standard deviation of dataOutlierFree per chemical element

setDataOutlierFree(bins, plat, rempl, method, nbOutliers): Aim: set dataOutlierFree; Arguments: bins = a numerical value corresponding to the time at which end the blank values, plat = a vector of two numerical values corresponding respectively to the time at which begin and end the plateau, rempl = value to replace outliers, method = the method used to detect outliers ("Tietjen.Moore Test", "SD criterion", "Rosner's test"), nbOutliers = nb of suspected outliers

setdata_standFinal(): Aim: set data_standFinalMean and data_standFinalSD

renderData(curve): Aim: render data without proceeding to their calculation; Argument: curve = a character string corresponding to the type of data to render ("Blank" for dataBlank, "Raw" for data, "Plateau" for dataPlateau, "Blank removed" for dataSuppBlank, ">LOD" for dataSupLOD, "Normalized" for dataNorm, "Outliers free" for dataOutlierFree); Output: a matrix of the required data

getData(curve, bins, plat, rempl, method, nbOutliers): Aim: calculate and render the required data ; Arguments: curve = a character string corresponding to the type of data to render (for more details, see the curve argument of the renderData function), bins = a numerical value corresponding to the time at which end the blank values, plat = a vector of two numerical values corresponding respectively to the time at which begin and end the plateau, rempl = value to replace outliers, method = the method used to detect outliers ("Tietjen.Moore Test", "SD criterion", "Rosner's test"), nbOutliers = nb of suspected outliers; Output: a matrix of the required data

elementR_data. elementR_sample.

## create a new elementR_standard object based on the "filePath" from a file containing data

filePath <- system.file("Example_Session/standards/Stand1.csv", package="elementR")

standardExample <- elementR_standard$new(filePath)

## Display the raw data 

standardExample$data