"distributional characteristics" is a correct and usable phrase in written English.
It refers to the specific attributes or features that describe how something is distributed, or spread out, within a certain context or system. Example: In a study of income distribution in the United States, the researchers analyzed the distributional characteristics of wealth within different demographic categories.
To ensure that the change in some parameters of the distribution happened we compared distributional characteristics of two subsamples drawn from each sample.
Under such empirical analysis, the zero-adjusted inverse Gaussian distribution is appropriate to reflect the distributional characteristics of crash rates and provide a new direction of approaches in the field of crash data analyses.
Descriptive statistics included distributional characteristics of the 33 HAPs and frequency distributions for demographic variables stratified on case control status.
Therefore, we estimated total expenditures using a generalized linear model (GLM) with a gamma distribution and log link function to account for the distributional characteristics of expenditure data.
EFA was conducted using the weighted least squares means and variance adjusted (WLSMV) under the specification of a censored normal distribution [ 30] for each of the items to account for distributional characteristics [ 32].
Due to these problems, little is known about the asymptotic distributional characteristics except in a naive approach.
The study examined several psychometric components of the measure, including dimensional structure, distributional characteristics, and indications of construct validity.
In its broadest sense, statistical semantics is concerned with semantic properties of words, phrases, sentences, and texts, engendered by their distributional characteristics in large text corpora.
Distributional characteristics (right skewness) and item difficulty (pm < 0.5) were also taken into account, considering the clinical implications of Young's EMS theory.
However, at unstable flow nearing capacity, both, following and non-following components of headways were observed to follow different distributional characteristics.
Virtually, both following and non-following headways are significant at such flow level and perhaps the trends in distributional characteristics are different for them.
