Interlaboratory Study
Bootstrap samples of a functional statistic
Function to compute the Cochran test statistic
Descriptive measures for functional data.
Function to compute the Grubbs test statistic
Function to estimate the univariate Mandel's h statistic
Functional Quality Control Data
It developes an object of class 'ils.fqcs'
Interlaboratoty Study
Function to calcute the Mandel's k statistic
Function to compute the AOV
Quality Control Data
Create an object of class 'lab.qcs' to perform statistical quality con...
This function is used to compute the FDA Mandel's h and k statistic
Detecting outliers for functional dataset
Plotting method for 'ils.fqcdata' objects
Plotting method for 'ils.fqcs' objects
Plot method for 'lab.qcdata' objects
Plot method for 'lab.qcs' objects
Plotting method for 'mandel.fqcs' objects
It performs interlaboratory studies (ILS) to detect those laboratories that provide non-consistent results when comparing to others. It permits to work simultaneously with various testing materials, from standard univariate, and functional data analysis (FDA) perspectives. The univariate approach based on ASTM E691-08 consist of estimating the Mandel's h and k statistics to identify those laboratories that provide more significant different results, testing also the presence of outliers by Cochran and Grubbs tests, Analysis of variance (ANOVA) techniques are provided (F and Tuckey tests) to test differences in means corresponding to different laboratories per each material. Taking into account the functional nature of data retrieved in analytical chemistry, applied physics and engineering (spectra, thermograms, etc.). ILS package provides a FDA approach for finding the Mandel's k and h statistics distribution by smoothing bootstrap resampling.