Calculate Wald og Likelihood based (profile likelihood) confidence intervals
lvm
-object.
Index of which parameters to calculate confidence limits for.
Confidence level
Logical expression defining whether to calculate confidence limits via the profile log likelihood
if FALSE and profile is TRUE, confidence limits are returned. Otherwise, the profile curve is returned.
Number of points to evaluate profile log-likelihood in
over the interval defined by interval
Interval over which the profiling is done
If FALSE the lower limit will not be estimated (profile intervals only)
If FALSE the upper limit will not be estimated (profile intervals only)
Additional arguments to be passed to the low level functions
A 2xp matrix with columns of lower and upper confidence limits
Calculates either Wald confidence limits: ˆθ±zα/2∗ˆσˆθ or profile likelihood confidence limits, defined as the set of value τ: logLik(ˆθτ,τ)−logLik(ˆθ)<qα/2
where qα is the α fractile of the χ21 distribution, and ˆθτ are obtained by maximizing the log-likelihood with tau being fixed.
bootstrap{lvm}
m <- lvm(y~x)
d <- sim(m,100)
e <- estimate(lvm(y~x), d)
confint(e,3,profile=TRUE)
#> 2.5 % 97.5 %
#> y~~y 0.5888514 1.026329
confint(e,3)
#> 2.5 % 97.5 %
#> y~~y 0.5547589 0.9802276
## Reduce Ex.timings
B <- bootstrap(e,R=50)
B
#> Non-parametric bootstrap statistics (R=50):
#>
#> Estimate Bias Std.Err 2.5 % 97.5 %
#> y 0.124504326 -0.007753062 0.073936733 0.008375347 0.288089457
#> y~x 1.061750034 0.013940880 0.074844578 0.949601761 1.235976345
#> y~~y 0.767493210 -0.026454597 0.100031344 0.584892411 0.986727053
#>