where δ is a vector of coefficients.
where β is a vector of coefficients to be estimated and ε i is the error term.
whose solution is a vector of coefficients that measure the information content of the examples and are nonzero only for the support vectors.
Where y it is a vector of dependent variables in country i at time t, X is a vector of exogenous variables, including the constant, and β is a vector of coefficients.
where P i is the likelihood probability function, X ' is a vector of explanatory variables, θ is a vector of coefficients of each explanatory variable, and ε i represents random error terms distributed at zero means and constant variance with unitary diagonal elements.
The values of these coefficients (b i, b ii and b ij ) are determined by Eq. (5): b = (X^{T} X)_{ - 1} X^{T} Y, (5 where b is a vector of coefficients, X is the design matrix for coded levels of variables and Y represents the vector of response (Khayet et al. 2011; Poroch-Seritan et al. 2011).
Where Xij is a matrix consisting of k explanatory variables for the i th of n observations plus a vector of ones for the intercept term and β j is a vector of coefficients to be estimated with dimensions (k + 1) × 1.
The probit model has the estimation form y = b'x + e, where y = 0 for farmers who answered "No" to the insurance purchase question; y = 1 for farmers who answered "Yes" to the insurance purchase question; x is a vector of explanatory variables; and b is a vector of coefficients.
where B, F, C and D represent energy choices obtained from biogas, firewood, charcoal and dried dung respectively; ( {y}_i^ ) represents the unobserved outcomes of energy choices, y i denotes the observed outcome of energy choice, x i is the vector of explanatory variables, and θ i is a vector of coefficients.
