fci.ml.boot {FuzzySTs} | R Documentation |
Estimates a fuzzy confidence interval by the Likelihood method
Description
Estimates a fuzzy confidence interval by the Likelihood method
Usage
fci.ml.boot(
data.fuzzified,
t,
distribution,
sig,
coef.boot,
mu = NA,
sigma = NA,
step = 0.05,
margin = c(5, 5),
breakpoints = 100,
plot = TRUE
)
Arguments
data.fuzzified |
a fuzzification matrix constructed by a call to the function FUZZ or the function GFUZZ, or a similar matrix. No NA are allowed. |
t |
a given numerical or fuzzy type parameter of the distribution. |
distribution |
a distribution chosen between "normal", "poisson", "Student" or "Logistic". |
sig |
a numerical value representing the significance level of the test. |
coef.boot |
a decimal representing the 1-sig-quantile of the bootstrap distribution of LR. |
mu |
if the mean of the normal distribution is known, mu should be a numerical value. Otherwise, the argument mu is fixed to NA. |
sigma |
if the standard deviation of the normal distribution is known, sigma should be a numerical value. Otherwise, the argument sigma is fixed to NA. |
step |
a numerical value fixed to 0.05, defining the step of iterations on the interval [t-5; t+5]. |
margin |
an optional numerical couple of values fixed to [5; 5], representing the range of calculations around the parameter t. |
breakpoints |
a positive arbitrary integer representing the number of breaks chosen to build the numerical alpha-cuts. It is fixed to 100 by default. |
plot |
fixed by default to "FALSE". plot="FALSE" if a plot of the fuzzy number is not required. |
Value
Returns a matrix composed by 2 vectors representing the numerical left and right alpha-cuts. For this output, is.alphacuts = TRUE.
Examples
data <- matrix(c(1,2,3,2,2,1,1,3,1,2),ncol=1)
MF111 <- TrapezoidalFuzzyNumber(0,1,1,2)
MF112 <- TrapezoidalFuzzyNumber(1,2,2,3)
MF113 <- TrapezoidalFuzzyNumber(2,3,3,4)
PA11 <- c(1,2,3)
data.fuzzified <- FUZZ(data,mi=1,si=1,PA=PA11)
Fmean <- Fuzzy.sample.mean(data.fuzzified)
fci.ml.boot(data.fuzzified, t = Fmean, distribution = "normal", sig= 0.05, sigma = 0.62,
coef.boot = 1.8225)