“…The second derivative K μ ′′ defines the covariance operator of P ( θ , μ ) and is given by the following expression where x ⊤ and K μ ′ ( θ ) ⊤ represent the transpose of the vectors x and K μ ′ ( θ ). The variance function of the NEF F ( μ ) is defined on M F ( μ ) by Its importance comes from the fact that it identifies the underling NEF and many works focused on the classifications of these families according to the form of their variance functions (see Casalis, 1996; Letac, 1992; Letac & Mora, 1990; Louati, Masmoudi, & Mselmi, 2015a; Morris, 1982; Mselmi, Kokonendji, Louati, & Masmoudi, 2018). Moreover, it is useful in the determination of the quasi‐likelihood function (or the quasi‐log‐likelihood function; see (McCullagh & Nelder, 1989), p. 325) which is defined by …”