controlChartData

<p>A set of fuzzy epistemic data concerning electronic circuit thickness, which is one of the most important
 quality characteristics in a process that produces electronic boards for vacuum cleaners.</p>

datasets

Random simulations of fuzzy numbers are still a challenging problem. The aim of this package is to provide the respective
procedures to simulate fuzzy random variables, especially in the case of the piecewise linear fuzzy numbers (PLFNs,
see Coroianua et al. (2013) <doi:10.1016/j.fss.2013.02.005> for the further details).
Additionally, the special resampling algorithms known as the epistemic bootstrap are provided (see Grzegorzewski and Romaniuk
(2022) <doi:10.34768/amcs-2022-0021>, Grzegorzewski and Romaniuk (2022) <doi:10.1007/978-3-031-08974-9_39>)
together with the functions to apply statistical tests and estimate various characteristics based on the epistemic bootstrap.
The package also includes a real-life data set of epistemic fuzzy triangular numbers.
The fuzzy numbers used in this package are consistent with the 'FuzzyNumbers' package.

Maciej Romaniuk

FuzzySimRes

Simulation and Resampling Methods for Epistemic Fuzzy Data

Przemyslaw Grzegorzewski

Abbas Parchami

Luis Carvalho

controlChartData function

<p>A list of 90 triangular fuzzy numbers (as defined in <code>FuzzyNumbers</code> package) that contains
30 samples, each of size three.
Each observation in the list has its label <code>X.y.z</code>, where <code>y</code> is the number of sample, and <code>z</code> is the
number of the element in this sample.</p>

Format

Fuzzy control charts data — controlChartData

Fuzzy control charts data

controlChartData: Fuzzy control charts data

Description

Usage

Arguments

Format