When the status of being vertically coordinated (VCi = 1) is not randomly assigned but stochastically depends on a set of observable characteristics, the propensity score can be implemented as a measure of conditional probability of being vertically coordinated conditional upon the observed variables, x, that include farm and farmer characteristics (reported in Table 1).
For example, the mutual information measure of conditional dependency between two variables is an elegant way of identifying and quantifying dependencies between elements in a system that may not be immediately obvious, especially in a complex situation involving a model with numerous inputs, nodes, and interactions.
These partial correlations are used as a measure of conditional independence and are the basis for graphical Gaussian models (GGMs).
When using the above-defined numerical measure of conditional entropy and the Chebyshev distance measure, we always found in our results that H(C| G1, G2) ≤ min{ H(C| G1), H(C| G2)}, consistent with information-theoretic facts [ 16].
Most of the characteristic variables were not significantly associated with composite measure of conditional acceptability in either site with only one exception; in Zambia, women who were not married or lived alone reported a higher conditional acceptability than their counterparts (P = 0.036).
Here the left hand side variable consists of direct measures of the conditional quantiles.
Here, the ARCH parameter denoted by β measures the reaction of conditional volatility to market shocks (i.e., it measures the variance response in exchange rate returns against appreciation or depreciation).
On the other hand, the GARCH parameter denoted by β measures the persistence of conditional volatility, regardless of shocks to the market.
This can be done employing the simulated distribution of the estimated measure of association, conditional on the sampling variances.
This test is based on the simulated distribution of the estimated measure of association, conditional on sampling variances.
