Hello I am trying to derive the second equation displayed in section 7.1 (or p. 41) of this article [link text][1] or equation (6.3) of this [book][2]. I've seen this in many documents discussing conditional sampling with copulae. Suppose $C(u_1,...u_d)$ is a d dimensional copula and $C_j(u_1,...u_j)=C(u_1,...u_j,1,...,1)$, $j \in {2,...,d-1}$ is the $j$ dimensional marginal copula. I am trying to prove the following relationship as in page 420 of this [book][3], $\mathbb{P}\left(U_{j}\leq u_{j},U_1=u_{1},\ldots,U_{j-1}=u_{j-1}\right)=\frac{\partial^{j-1}C_{j}\left(u_{1},\ldots,u_{j}\right)}{\partial u_{1},\ldots,\partial u_{j-1}}$ Maybe something along the lines of, $\mathbb{P}\left(U_{j}\leq u_{j},U_1=u_{1},\ldots,U_{j-1}=u_{j-1}\right)$ $=\lim_{\triangle u_{1},\ldots,\triangle u_{j-1}\rightarrow0}\mathbb{P}\left(U_{j}\leq u_{j},u_{1}\leq U_{1}\leq u_{1}+\triangle u_{1},\ldots,u_{j-1}\leq U_{j-1}\leq u_{j-1}+\triangle u_{j-1}\right) $ then the paper i'm reading tells me if this is right it should equal $=\lim_{\triangle u_{1},\ldots,\triangle u_{j-1}\rightarrow0}\frac{C_{j}\left(u_{1}+\triangle u_{1},\ldots,u_{j-1}+\triangle u_{j-1},u_{j}\right)-C\left(u_{1},\ldots,u_{j}\right)}{\triangle u_{1}\cdots\triangle u_{j-1}}$ ... (*) Where the fact the copula $C_j$ is the joint distribution of $j$ uniform random variables, $U_1,...,U_j$ is used. But I dont quite understand where the denominator in (*) $\triangle u_{1}\cdots\triangle u_{j-1}$ comes from?? In fact the derivation in the paper goes against my understanding of probability. For example how does the author divide by $\mathbb{P}\left(U_{j}\leq u_{j},U=u_{1},\ldots,U_{j-1}=u_{j-1}\right)$ in the derivation. I would have imagined since the $u_i$'s are continuous this quantity would be 0... but how come its not?? [1]: http://ta.twi.tudelft.nl/users/vuik/numanal/kort_afst.pdf [2]: http://books.google.co.uk/books?id=0dyagVg20XQC&pg=PA182&dq=6.3+conditional+sampling+copula&hl=en&ei=AvrOTayfGMuBhQfV3-HyDA&sa=X&oi=book_result&ct=result&resnum=1&ved=0CDcQ6AEwAA#v=onepage&q=6.3%2520conditional%2520sampling%2520copula&f=false [3]: http://books.google.co.uk/books?id=I_Ua05TV1M0C&printsec=frontcover&dq=statistics+of+financial+markets&hl=en&ei=dwPPTZ3uHsK6hAfGyOD9DA&sa=X&oi=book_result&ct=result&resnum=1&ved=0CEIQ6AEwAA#v=snippet&q=conditional%2520inverse%2520method&f=false