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 |
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
.
1 2 3 4 5 6 7 8 9 | ## 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
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