Valid confidence intervals for $μ, σ$ when there is only one observation available

Portnoy (2019) considered the problem of constructing an optimal confidence interval for the mean based on a single observation $\, X \sim {\cal{N}}(μ, \, σ^2) \,$. Here we extend this result to obtaining 1-sample confidence intervals for $\, σ\,$ and to cases of symmetric unimodal distributions and of distributions with compact support. Finally, we extend the multivariate result in Portnoy (2019) to allow a sample of size $\, m \,$ from a multivariate normal distribution where $m$ may be less than the dimension.

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