Scaling p_T Distribution in Small Rapidity Region and Pseudorapidity Asymmetry for Charged Hadron in d+Au Collisions at (S_(NN))^(1/2)=200 GeV

With the experimental data from STAR program on the centrality dependence of the PT spectra of charged hadron produced in d＋Au collisions at √^8NN=200 GeV, we show that there also exists a scaling distribution in the backward rapidity regions. Using this scaling distribution, we get the theoretical psedorapidity asymmetry which is basically in agreement with STAR data in the regions of 0≤｜η｜≤0.5 and 0.5 ≤｜η｜≤1. No theoretical models are used in any part of this phenomenological analysis.

Scaling of weighted spectral distribution in weighted small-world networks

Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution（W SD） have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the W SD in a deterministic weighted scale-free small-world network model and find that the W SD grows sublinearly with increasing network order（i.e., the number of nodes） and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the W SD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents.

Spatial Distribution Pattern of Populations of Isoetes sinensis Palmer, an Endangered Quillwort in China

The distribution pattern of Isoetes sinensis populations was investigated in relation to its biological characteristics such as age structure and regeneration mode, and the microenvironment. Contagious distribution pattern was found in populations of all sizes. Under the same climatic and site conditions, the heterogeneity of mieroenvironment resulting from the different depths of water and soil erosion significantly affecred the type and scale of distribution patterns of Isoetes sinensis populations. Even at the same site, the center and the edges of the water body had different effects on the distribution pattern of the plants. As one of the co-dominants, the distribution of Isoetes sinensis in communities was affected by other dominant species, especially by the evergreen grass species. Water is the major factor determining the distribution pattern of lsoetes sinensis in various communities. The pattern of contagious distribution was observed in different size of populations of I.sinensis, however the Lloyd indices obtained for the populations of various sizes differed significantly.

Distribution Pattern Scale of Natural Toona ciliata Population

In order to research the population distribution pattern of endangered species Toona ciliata Roem., the sampling quadrats of 5 mx5 m and 3 m×3 m in size, accurate to 1 mxl m, were established in 2 newly-found only existing T. cili- ata Roem. communities （T1 and T2） with contiguous grid quadrate method, in the Nanhe River valley, Gucheng County. By X2 test, t-test of distribution coefficient Cx method, and F test of Morisita pattern index Iδ whether the distribution patterns of the T. ciliata Roem. populations conformed to Poisson distribution were checked. The results indicated that, population T1 was in Poisson distribution under 5 m×5 m and 3 m×3 m in size by Cx and 16 methods, but in clumped distribution pattern un- der 5 m×5 m in size by the Chi-square test; however, the population was in Pois- son distribution under the dimension of 3 m×3 m. Population T2 under human dis- turbance had higher population density, indicating clumped distribution under 3 above-mentioned tests. If Chi-square test is satisfied, a distribution pattern is in Poisson distribution, and size and quantity of sampling quadrats should be given pri- ority to; and if df is greater, both theoretical values and observed values tend to- wards normal distribution more probably, and the test of distribution pattern, there- fore will be more dependable.

Joint modelling of location and scale parameters of the skew-normal distribution

Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.

Variable Selection for Robust Mixture Regression Model with Skew Scale Mixtures of Normal Distributions

In this paper, we propose a robust mixture regression model based on the skew scale mixtures of normal distributions (RMR-SSMN) which can accommodate asymmetric, heavy-tailed and contaminated data better. For the variable selection problem, the penalized likelihood approach with a new combined penalty function which balances the SCAD and l2 penalty is proposed. The adjusted EM algorithm is presented to get parameter estimates of RMR-SSMN models at a faster convergence rate. As simulations show, our mixture models are more robust than general FMR models and the new combined penalty function outperforms SCAD for variable selection. Finally, the proposed methodology and algorithm are applied to a real data set and achieve reasonable results.