Stopping rules for the estimation of the parameters of bivariate and trivariate binomial distributions

In this work one step look-ahead rules for the estimation of the parameters of the bivariate and trivariate distributions are given. They turn out to be asymptotically optimal and may be useful in many statistical contexts, for example, in statistical quality control and customer satisfaction analyses.binominal distribution, estimation, success categorization

On the spectrum of genera of quotients of the Hermitian curve

We investigate the genera of quotient curves $\mathcal H_q/G$ of the $\mathbb F_{q^2}$-maximal Hermitian curve $\mathcal H_q$, where $G$ is contained in the maximal subgroup $\mathcal M_q\leq{\rm Aut}(\mathcal H_q)$ fixing a pole-polar pair $(P,\ell)$ with respect to the unitary polarity associated with $\mathcal H_q$. To this aim, a geometric and group-theoretical description of $\mathcal M_q$ is given. The genera of some other quotients $\mathcal H_q/G$ with $G\not\leq\mathcal M_q$ are also computed. Thus we obtain new values in the spectrum of genera of $\mathbb F_{q^2}$-maximal curves. A plane model for $\mathcal H_q/G$ is obtained when $G$ is cyclic of order $p\cdot d$, with $d$ a divisor of $q+1$

Maximal curves from subcovers of the GK-curve

For every $q=n^3$ with $n$ a prime power greater than $2$, the GK-curve is an $\mathbb F_{q^2}$-maximal curve that is not $\mathbb F_{q^2}$-covered by the Hermitian curve. In this paper some Galois subcovers of the GK curve are investigated. We describe explicit equations for some families of quotients of the GK-curve. New values in the spectrum of genera of $\mathbb F_{q^2}$-maximal curves are obtained. Finally, infinitely many further examples of maximal curves that cannot be Galois covered by the Hermitian curve are provided

Technological change and industry competitiveness through the evolution of localised comparative advantages - The case of Italy

The influence of technological change on industry performances is nowadays being increasingly investigated under the broad category of "national systemic competitiveness". Moreover theoretical works have shown that the relationship between technology and economic performance not only takes different forms in different socio-economic contexts, but is also powerfully influenced by the way that innovation processes evolve over time along strongly localised patterns. The present study is focused on the evolution of trade competitiveness of the manufacturing sector in Italy over the past ten years and addresses to the role played by localised comparative advantages in shaping the model of national competitiveness. The data used in the analysis, drawn by the Enea Observatory on high tech industries, are based on trade statistics at the SITC five digit level and are spatially referenced to the Italy NUT3 regional partition. The effects of localised trade specialisation on manufacturing competitiveness are first assessed through spatial econometric tecniques. Spatial variation in the relationships found is further explored in order to give additional hints on the specific contribution of localised comparative advantages. According to major trends which have recently characterised manufacturing trade competitiveness in Italy, the analysis is expected to bring into evidence significant changes in the contribution of industrial localities to national competitiveness.