The empirical likelihood inference is extended to a class of semiparametric models for stationary, weakly dependent series. A partially linear single-index regression used the conditional mean series given its past, and present past values vector covariates. parametric model variance added capture further nonlinear effects. We propose suitable moment equations which characterize model. derive a...

we denote by $ls[n](t,k,v)$ a large set of $t$-$(v,k,lambda)$ designs of size $n$, which is a partition of all  $k$-subsets ofa $v$-set into $n$ disjoint  $t$-$(v,k,lambda)$ designs and$n={v-t choose k-t}/lambda$.   we use the notation$n(t,v,k,lambda)$ as the maximum possible number of mutuallydisjoint cyclic $t$-$(v,k,lambda)$designs. in this paper we givesome new bounds for $n(2,29,4,3)$ and ...