Calculate confidence limits for parameters
Calculate Wald og Likelihood based (profile likelihood) confidence intervals
## S3 method for class 'lvmfit' confint( object, parm = seq_len(length(coef(object))), level = 0.95, profile = FALSE, curve = FALSE, n = 20, interval = NULL, lower = TRUE, upper = TRUE, ... )
object |
|
parm |
Index of which parameters to calculate confidence limits for. |
level |
Confidence level |
profile |
Logical expression defining whether to calculate confidence limits via the profile log likelihood |
curve |
if FALSE and profile is TRUE, confidence limits are returned. Otherwise, the profile curve is returned. |
n |
Number of points to evaluate profile log-likelihood in
over the interval defined by |
interval |
Interval over which the profiling is done |
lower |
If FALSE the lower limit will not be estimated (profile intervals only) |
upper |
If FALSE the upper limit will not be estimated (profile intervals only) |
... |
Additional arguments to be passed to the low level functions |
Calculates either Wald confidence limits:
\hat{θ} \pm z_{α/2}*\hatσ_{\hatθ}
or profile likelihood confidence limits, defined as the set of value τ:
logLik(\hatθ_{τ},τ)-logLik(\hatθ)< q_{α}/2
where q_{α} is the α fractile of the χ^2_1 distribution, and \hatθ_{τ} are obtained by maximizing the log-likelihood with tau being fixed.
A 2xp matrix with columns of lower and upper confidence limits
Klaus K. Holst
bootstrap{lvm}
m <- lvm(y~x) d <- sim(m,100) e <- estimate(lvm(y~x), d) confint(e,3,profile=TRUE) confint(e,3) ## Reduce Ex.timings B <- bootstrap(e,R=50) B
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