The particle filter based on random number searching algorithm for parameter estimation

This article addresses the issue of parameter estimation in linear system in the presence of Gaussian noises, under which the random number searching algorithm (LJ (Luus and Jaakola) algorithm) is combined with the Rao-Blackwellised particle filter (RBPF) algorithm. This yields the so-called RBPF algorithm based on LJ (RBPF-LJ). Unlike the mature alternatives of generic particle filter, the parameter particles of RBPF-LJ are set as random numbers that search in the parameter value scope, which is regulated based on the estimation result to track the changes of the unknown parameter. The contrasting simulations show that the proposed RBPF-LJ outperform the RBPF as well as the particle filter based on kernel smoothing contraction algorithm on the estimation of the dynamically linear or nonlinear parameter and it can obtain the similar estimation results on the static parameter if some coefficients are regulated.     

A method to generate autocorrelated uniform random numbers

We present a simple, fast method to generate autocorrelated uniform random numbers. The “sum of uniforms” method adds a pair of U(0,1) random numbers, transforms the sum to a third U(0,1) random number, and uses this third random number as one member of the next pair. The method produces any desired level of positive or negative correlation between successive random numbers.     

殖民生态视角下林芙美子的森林情怀

林芙美子是日本昭和时期著名女作家,在日本的近代文学史上具有举足轻重的作用。林芙美子的文学记述中呈现了若干森林元素,表达了她对森林的挚爱和向往,客观再现了日本殖民时代对森林资源的攫取与侵蚀,并流露出她对人与自然关系的生态直觉意识。林芙美子曾是日本对外侵略战争的积极支持者,但对于日本殖民造成的森林灾难,她有一种源自内心的悲哀和抵触。这种森林情怀成为整体把握林芙美子文学思想不可忽略的一个侧面。     

Bayesian exponential random graph models with nodal random effects

We extend the well-known and widely used exponential random graph model (ERGM) by including nodal random effects to compensate for heterogeneity in the nodes of a network. The Bayesian framework for ERGMs proposed by Caimo and Friel (2011) yields the basis of our modelling algorithm. A central question in network models is the question of model selection and following the Bayesian paradigm we focus on estimating Bayes factors. To do so we develop an approximate but feasible calculation of the Bayes factor which allows one to pursue model selection. Three data examples and a small simulation study illustrate our mixed model approach and the corresponding model selection.     

On accurate and precise generation of generalized Poisson variates

This article is concerned with comparison of a few random variate generation techniques for the generalized Poisson distribution. An evaluation is conducted on the degree of proximity between the estimates for its two distributional parameters and first four moments, and the specified or computed true population values via commonly accepted accuracy and precision measures in a simulated setting.     

Precise asymptotics on spectral statistics of random matrices

This paper focuses on the limiting properties of the spectral statistics of Wigner matrices and sample covariance matrices. Following the ideas of Gut and Spaˇtaru (2000a, b), Gut and Steinebach (2013) and Chow (1988) on precise asymptotics of i.i.d. random variables in the context of complete convergence and moment convergence, we will establish the corresponding results on the spectral statistics of random matrices.     

Some results on random design regression with long memory errors and predictors

This paper studies nonparametric regression with long memory (LRD) errors and predictors. First, we formulate general conditions which guarantee the standard rate of convergence for a nonparametric kernel estimator. Second, we calculate the mean integrated squared error (MISE). In particular, we show that LRD of errors may influence MISE. On the other hand, an estimator for a shape function is typically not influenced by LRD in errors. Finally, we investigate properties of a data-driven bandwidth choice. We show that averaged squared error (ASE) is a good approximation of MISE; however, this is not the case for a cross-validation criterion.     

Random Coefficients Estimation of Average Total Product Costs for Multiproduct Firms

The problem of estimating the mean average total cost of each output for multiproduct firms in an industry is addressed. The identity that defines total cost for each firm as the product of output levels multiplied by their respective average total costs is viewed as a random-coefficients model. A random coefficients regression estimator is used to estimate mean average total output costs. Solutions to problems arising with this method in empirical studies are discussed. An application of the approach to data from cash grain farms in Illinois shows that the method gives reliable estimates for per-unit output production costs with considerably fewer data requirements than current methods of cost estimation.     

A generalization of the donnelly-tavare-griffiths formula

We give a generalization of the one form of the Donnelly-Tavaré-Griffiths(DTG) formula. It contains not only this DTG formula but also the conditional distribution of the formula given the some first components. We can construct it using a simple urn model. For the generalization of the DTG formula, its probability distributions including marginal and conditional distributions, the related statistics and their asymptotic properties are discussed.     

Environmental security and labor migration in Nepal

Do changes in environmental security that result from declining access to forest resources shape labor migration in a context where household production and consumption are intimately dependent on natural resources? Using 1996 household data from the Chitwan Valley of Nepal, we examined if a decrease in access to firewood increased the likelihood of migration of individuals for work. The results of multinomial logistic regression showed that, environmental insecurity was a significant predictor for migration regardless of destination, domestic or international. Labor requirements for household maintenance also played an important role in the decision to migrate. Management of forest resources and poverty alleviation by providing firewood substitutes and economic opportunities at the local level is likely to change the labor migration flow, which could be an important issue for future research.