Learn R Programming

censNID (version 0-0-1)

cenNID: mle estimation for censored normal

Description

MLE estimation using AS 138 for censored and confined normal.

Usage

cenNID(y, L=rep(-Inf, length(y)), U=rep(Inf,length(y)))

Arguments

y
observations
L
lower bound for each observation that is equal to -Inf when none, default -Inf
U
upper bound for each observation that is equal to Inf when none, default Inf

Value

a list with the following components:
est
matrix with mean and sd and their se
covMat
covariance matrix
nobs
number of complete observations
itercount
number of iterations
ifault
fault indicator. 0-converged. -1:convergence not obtained in default number of allowed iterations. -2:fewer than 2 complete obserations. -3:error with confined estimator initial values (should not occur in R version). -4:invalid specification for limits with confined observation.

References

M. S. Wolynetz (1979). Algorithm AS 138: Maximum Likelihood Estimation from Confined and Censored Normal Data. Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 28, No. 2, pp. 185-195

See Also

censNID

Examples

Run this code
set.seed(32173217)
n<-100
z <- rnorm(n)
U <- rep(Inf, n)
L <- rep(-Inf, n)
cy <- -1
ind <- z > cy
m <- sum(as.integer(ind))
y <- c(z[ind], rep(cy, n-m))
L[(m+1):n] <- cy
cenNID(y, L, U) 

Run the code above in your browser using DataLab