cenNID: mle estimation for censored normal

Description Usage Arguments Value Author(s) References See Also Examples

Description

MLE estimation using AS 138 for censored and confined normal.

Usage

1
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.

Author(s)

A. I. McLeod aimcleod@uwo.ca

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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
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) 

Example output

$est
           mle    se(mle)
mean 0.2446342 0.08103375
sd   0.7432756 0.05629631

$CovMat
             mean           sd
mean 0.0065664684 0.0002920137
sd   0.0002920137 0.0031692742

$nobs
[1] 81 19  0  0

$iterCount
[1] 8

$ifault
[1] 0

censNID documentation built on May 2, 2019, 6:11 a.m.

Related to cenNID in censNID...