The reasons that motivated the selection and categorisation of each indicator are described and the proposed system is compared with other existing indicator systems.
According to Formula (10), variation of the time correlation indicator is described as Δq t = q t − q t ′: Delta {q}_t=frac{sum limits_{i=1}^nleft(sum limits_{t=1}^{v_i^{hbox{f}_tleft(Xleft i,tright)right -sum limits_{t=1}^{v_i}{f}_tleft(Xleft(i,tright -sumt)right)}{N}, (15)in which q t and q t ′ are independent to each other and satisfy the binomialimitsribution respectively.
The calculations for each indicator are described below.
The risk factors in each indicator are described in Table 1.
Each indicator was described in terms of numerator, denominator, target population, exclusion criteria, definition of terms involved, sources of data and bibliography [ 42].
It is conceivable that an indicator was described by a specific statistic such as a median because of an underlying non-normal distribution, in order to permit sound statistical inference.
Analyze of the heat transfer indicators were described by tabular values and by one year chart for Braşov region, in Romania.
The equation's descriptors and their associated indicators were described in the previous paragraphs.
The distribution (median and IQR) of the districts' sociodemographic indicators were described for the districts within and outside 50 km buffer; these indicators included the proportion of rural population, ranking, proportion of population with low SOLI and proportion of people living below the poverty line.
In this paper, only some selected indicators are described in detail.
