Description Usage Arguments Details Value References See Also Examples
This function is the main function of package ANOVA.TFNs
it can easily test one-way Analysis of Variance based on Triangular Fuzzy observation on the basis of m=1,2,3,... by (Parchami et al., 2017, 2018) method.
1 |
Data |
a matrix with dim=c(n, 4) and |
m |
a positive integer number which related to the weight of distance between two cuts of fuzzy numbers, and its default is m=1. For more details see (Parchami et al., 2017, 2018). |
sig.level |
the significance level of test with default sig.level=0.05. |
fig |
a logical argument with default TRUE. If fig=TRUE, the membership functions of inputted fuzzy data will be depicted in a figure as presented in |
Function FANOVA
compute all needed statistics for Fuzzy ANOVA test which introduced in (Parchami et al., 2018) and is able report the FANOVA table and the p-value of FANOVA test.
Function FANOVA
returned the values:
table |
Fuzzy ANOVA Table which contains details of FANOVA based on Triangular fuzzy data |
f_ob |
The observed value of test statistic in FANOVA test, which sometimes denoted by F-statistic |
p_value |
The p-value in FANOVA test which is equal to the above tail area of F-statistic |
FANOVA_test_result |
Final report (Accept/Reject) H_0 at the considered significance level |
Gagolewski, M., Caha, J. (2015) FuzzyNumbers Package: Tools to deal with fuzzy numbers in R. R package version 0.4-1, https://cran.r-project.org/web/packages=FuzzyNumbers
A. Parchami, M.R. Nourbakhsh, M. Mashinchi (2017) Analysis of Variance in Uncertain Environments, Complex & Intelligent Systems, Volume 3, Number 3, 189-196, DOI: 10.1007/s40747-017-0046-8
A. Parchami, M. Mashinchi, C. Kahraman (2018) An Implication of Fuzzy ANOVA in Vehicle Battery Manufacturing, Journal of Enterprise Information Management, Preprint.
FuzzyNumbers
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | # Example 1:
data(Data)
head(Data)
FANOVA( Data )
FANOVA( Data, fig=FALSE )
FANOVA( Data, m=2, sig.level=0.1 )
FANOVA( Data, fig=FALSE )$p_value
FANOVA( Data, fig=FALSE )$FANOVA_test_result
FANOVA( Data, fig=FALSE )[[1]] # Only FANOVA Table
# Example 2:
t <- 20
f <-p <- c()
for(i in 1:t){
f[i] <- FANOVA(Data, m=i, fig=FALSE)$f_ob
p[i] <- FANOVA(Data, m=i, fig=FALSE)$p_value
}
par(mfcol=c(2,1))
plot(1:t, f, main="FANOVA test statistics (f) v.s m (1:20)")
plot(1:t, p, main="p-value v.s m (1:20)")
par(mfcol=c(1,1))
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