The present study addresses this issue through an assessment of the confidence intervals on reliability indices using likelihood ratio statistics for cases where the capacity and/or demand models are derived from finite samples of data, expert opinion, or simulations.
These Bayesian predictions incorporate all uncertainty due to finite sampling of the data and prior uncertainty about the parameters.
A spectrum is represented as a finite sampling of an independent, identically distributed (in time) random process defined on a finite outcome space D, where the elements of D correspond to the m/ z data points established by the acquisition hardware.
In practice the time-integrals in (18) are realized by a finite sampling of the time interval.
The proposed algorithm with finite sampling data can be implemented as follows.
However, in practice with finite sample data, the true model is not known, and the models most suitable for estimation and prediction may differ.
Mostly a fast Fourier transform is computed for finite sequence of data sample [ 4].
Fourier transform is a basic tool for analyzing biological signals and is computed for a finite sequence of data sample.
We investigate finite sample performance of each of the estimators by varying the sample size within each unique simulation experiment.
However, there has been some progress in developing both large sample and finite sample robustness of SEM parameters in handling non-normal data and outliers [ 25, 26].
No finite amount of data will ever be able to narrow the possibilities down to just a single function or indeed, any finite number of candidate functions, from which the distribution of data points we have might have been generated.
