The significance with which an array is matched with a pathprint, or with a consensus pathprint, is then calculated using the P-value, based on the normal distribution function based on this estimated distribution.
It is based on estimating, via randomization, the empirical probability distribution for the max-statistic (e.g. the maximum of a t), under the null hypothesis.
Classification techniques can be probabilistic, if they are based on estimates of probability distributions.
Specifically, following the Bayesian framework, an initial quantification of the plausibility of each possible value of the parameters of interest was summarised in a probability distribution (prior distribution), based on estimates of sensitivity and specificity obtained from the validation study in the general population sample and on prevalence obtained from previous population studies.
Such tests make inferences about the parameters of the distribution based on estimates obtained from the data.
Statistical tests were performed using Z statistics with standardized normal distribution based on estimates of Gini-Simpson diversity.
Among the five heterogeneous variances MTC model, the informed variances model based on frequentist approximate distributions produced variance estimates closest to the frequentist ones and had the posterior variance distributions with the highest precision.
Based on our estimated afterslip distribution, coseismic slip and the interplate coupling distribution of previous studies, we suggest that afterslip following the 2003 Tokachi-oki earthquake released accumulated strain due to interplate coupling in the source region of the seventeenth-century tsunamigenic giant earthquake partially but much of it still remains.
Posterior distributions were estimated based on uninformative prior distributions (normal distributions with mean 0 and standard deviation 100 for parameter means; inverse gamma distributions with mean 1 and variance 10,000 for variance of measurement error; uniform distributions with range 0 to 100 for standard deviation of random intercepts).
The reliability analysis in this study is based on the distributions estimated for dead, live and wind loads.
