Bivariate non-central negative binomial distribution: Another generalisation

Summary Another bivariate generalisation (Type V) of the non-central negative binomial distribution is considered. This generalisation is constructed (i) as a latent structure model; (ii) as an extension of an accident proneness model investigated by Edwards/Gurland (1961); and (iii) as a reversible stochastic counter model. The third construction gives, as a result, an apparently new formulation of the Edwards/Gurland model. The probabilities, moments, recurrence formulas and some properties are given. An application to the data used by Holgate (1966) is considered.     

Bounds for the median of the negative binomial distribution

Summary Bounds are obtained for the median of the negative binomial distribution which are valid for all possible parameter values of the distribution when the median is defined as inf {x: P(X≤x)≥1/2}.     

Complete sufficiency and maximum likelihood estimation for the two-parameter negative binomial distribution

The difficult estimation problem associated with the two-parameter negative binomial distribution is discussed. The order statistic is shown to be minimal sufficient but not complete. It is proven that there is at least one maximum likelihood estimator of the parameterk when the second sample moment is greater than the sample mean. Contours and three-dimensional graphs of the natural logarithm of the likelihood function provide further insight into the estimation problem.     

On a test of homogeneity for samples from a negative binomial distribution

Summary An exact test is proposed for the equality of probabilities of an event in a series of independent trials, each drawn from a negative binomial distribution with a specified number of successes. The power function of this conditional test is also derived, as well as an approximate test for homogeneity.     

On some properties of the linear function Poisson binomial and negative binomial distributions

Summary A general model in fluctuations of sums of random variables leading, under certain assumptions, to each of the generalized and linear function Poisson, binomial and negative binomial distributions is presented. Moreover the generating functions and the factorial moments of the linear function Poisson, binomial and negative binomial distributions are obtained in close forms and certain distributional properties are discussed.     

A fixed sample size selection procedure for negative binomial populations

Summary A fixed sample size procedure for selecting the ‘best’ ofk negative binomial populations is developed. Selection is made in such a way that the probability of correct selection is at leastP* whenever the distance between the probabilities of success is at leastδ*. The exponentr is assumed to be known and the same for all populations. Extensive computer calculations* were employed to obtain the exact least favorable configuration. The smallest sample sizes needed to meet specifications (P*,δ*) are tabulated forr=1 (1)5;δ*=0.05 (0.05) 0.55 andP*=0.75, 0.80, 0.90, 0.95, 0.98, 0.99 involvingk=3 (1) 6, 8, 10 populations. All the computations were carried out on the Alabama Supercomputer. Part of this work was completed when the authors were at the Department of Statistics, Oklahoma State University, Stillwater, OK 74078.     

Estimating features of a distribution from binomial data

We propose estimators of features of the distribution of an unobserved random variable W. What is observed is a sample of Y,V,X where a binary Y equals one when W exceeds a threshold V determined by experimental design, and X are covariates. Potential applications include bioassay and destructive duration analysis. Our empirical application is referendum contingent valuation in resource economics, where one is interested in features of the distribution of values W (willingness to pay) placed by consumers on a public good such as endangered species. Sample consumers with characteristics X are asked whether they favor (with Y=1 if yes and zero otherwise) a referendum that would provide the good at a cost V specified by experimental design. This paper provides estimators for quantiles and conditional on X moments of W under both nonparametric and semiparametric specifications.     

Locally D- and c-optimal designs for Poisson and negative binomial regression models

The research on optimal experimental designs for nonlinear regression models is of great interest because these models are used to characterize chemical, biological or agricultural phenomena. Much of them involve an exponential decay. In this paper, locally D- and c-optimal designs are derived analytically for Poisson and negative binomial regression models.     

Efficient parameter estimation for independent and INAR(1) negative binomial samples

We consider moment based estimation methods for estimating parameters of the negative binomial distribution that are almost as efficient as maximum likelihood estimation and far superior to the celebrated zero term method and the standard method of moments estimator. Maximum likelihood estimators are difficult to compute for dependent samples such as samples generated from the negative binomial first-order autoregressive integer-valued processes. The power method of estimation is suggested as an alternative to maximum likelihood estimation for such samples and a comparison is made of the asymptotic normalized variance between the power method, method of moments and zero term method estimators.     

Some notes on discount factor restrictions for dynamic optimization problems

We consider dynamic optimization problems on one-dimensional state spaces. Under standard smoothness and convexity assumptions, the optimal solutions are characterized by an optimal policy function h mapping the state space into itself. There exists an extensive literature on the relation between the size of the discount factor of the dynamic optimization problem on the one hand and the properties of the dynamical system x_t+1=h(x_t) on the other hand. The purpose of this paper is to survey some of the most important contributions of this literature and to modify or improve them in various directions. We deal in particular with the topological entropy of the dynamical system, with its Lyapunov exponents, and with its periodic orbits.     

A generalized correlated binomial distribution with application in multiple testing problems

A typical microarray experiment often involves comparisons of hundreds or thousands of genes. Since a large number of genes are compared, simple use of a significance test without adjustment for multiple comparison artifacts could lead to a large chance of false positive findings. In this context, Tsai et al. (Biometrics 59:1071–1081, 2003) have presented a model that studies the overall error rate when testing multiple hypotheses. This model involves the distribution of the sum of non-independent Bernoulli trials and this distribution is approximated by using a beta-binomial structure. Instead of using a beta-binomial model, in this paper, we derive the exact distribution of the sum of non-independent and non-identically distributed Bernoulli random variables. The distribution obtained is used to compute the conditional false discovery rates and the results are compared to those obtained, in Table 3, by Tsai et al. (Biometrics 59:1071–1081, 2003).     

长春富豪花园住宅小区建设与管理拾珍

长春市富豪花园住宅小区是长春市的规模式的成熟社区 ,曾经获得政府的多次褒奖。本文总结其多年来本着“以人为本”的理念进行精品建设和管理的事迹。     

车门尼槽设计的几点注意事项

文章介绍了两款尼槽在整车实验和生产过程中出现的问题,通过对尼槽结构、口型、表面处理与车门装配关系的分析,总结了几点注意事项。     

Some characterizations of the bivariate normal distribution

Summary In this note assuming the conditional normality of one component of a bivariate random vector given the value of the other component some characterizations of the joint normality of the random vector are given.     

Some immediate - but negative - effects of openness on product development performance

This paper charts an unnoticed theme in the current debate on open innovation, namely the foundational question whether increasing openness is beneficial? The paper approaches this question by conceptualising the degree of ‘openness’ and analyses the importance of increasing degrees of openness for NPD performance. Inter-organizational relationships in New Product Development lay the foundation for operationalising openness because these represent important sources of ideas and knowledge in purposive inbound open innovation. This exploratory paper finds that on immediate NPD performance measures the single firm strategy is performing better than the collaborative strategy. However, we also find that the use of internal and external relationships is highly correlated and that these interact with each other. Finally, with increasing degrees of openness the product development projects are slower than the norm in the industry, slower than what is usual for the firm’s projects and had higher cost than the norm in the industry and the firm’s usual projects. These results offer a more critical perspective on openness and NPD performance than the literature on the open innovation paradigm suggests. The paper discusses these results and offers some challenges for management and research of open innovation.