Fisher's repeated normal integral function and shape distributions

SUMMARY Fisher has presented various applications of the repeated integral of the normal distribution function. A new application has appeared in shape distributions. This work has led to the search for an explicit expression for the repeated normal integral function in place of an infinite series expansion for this function first given by Fisher. We provide an explicit expression for this function with a finite number of terms.     

Design and evaluation of skip-lot sampling inspection plans with double-sampling plan as the reference plan

This paper presents a design for skip-lot sampling inspection plans with the double-sampling plan as the reference plan, so as to reduce the sample size and produce more efficient plans in return for the same sampling effort. The efficiency of the proposed plan compared with that of the conventional double-sampling plan is also discussed. The need for smaller acceptance numbers under the plan is highlighted. Methods of selecting the plan indexed by the acceptable quality level and limiting quality level, and by the acceptable quality level and average outgoing quality level are also presented.     

Latin hypercube sampling with multidimensional uniformity

Complex models can only be realized a limited number of times due to large computational requirements. Methods exist for generating input parameters for model realizations including Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS). Recent algorithms such as maximinLHS seek to maximize the minimum distance between model inputs in the multivariate space. A novel extension of Latin hypercube sampling (LHSMDU) for multivariate models is developed here that increases the multidimensional uniformity of the input parameters through sequential realization elimination. Correlations are considered in the LHSMDU sampling matrix using a Cholesky decomposition of the correlation matrix. Computer code implementing the proposed algorithm supplements this article. A simulation study comparing MCS, LHS, maximinLHS and LHSMDU demonstrates that increased multidimensional uniformity can significantly improve realization efficiency and that LHSMDU is effective for large multivariate problems.     

A multiple test for comparing two treatments with control: Interval hypotheses approach

In biological experiments, multiple comparison test procedures may lead to a statistically significant difference in means. However, sometimes the difference is not worthy of attention considering the inherent variation in the characteristic. This may be due to the fact that the magnitude of the change in the characteristic under study after receiving the treatment is small, less than the natural biological variation. It then becomes the job of the statistician to design a test that will remove this paradox, such that the statistical significance will coincide with the biological one. The present paper develops a multiple comparison test for comparing two treatments with control by incorporating within-person variation in forming interval hypotheses. Assuming common variance (unknown) for the three groups (control and two treatments) and the width of the interval as intra-individual variation (known), the distribution of the test statistic is obtained as bivariate non-central t . A level f test procedure is designed. A table of critical values for carrying out the test is constructed for f = 0.05. The exact powers are computed for various values of small sample sizes and parameters. The test is powerful for all values of the parameters. The test was used to detect differences in zinc absorption for two cereal diets compared with a control diet. After application of our test, we arrived at the conclusion of homogeneity of diets with the control diet. Dunnett's procedure, when applied to the same data, concluded otherwise. The new test can also be applied to other data situations in biology, medicine and agriculture.     

A robust multivariate measurement error model with skew-normal/independent distributions and Bayesian MCMC implementation

Skew-normal/independent distributions are a class of asymmetric thick-tailed distributions that include the skew-normal distribution as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in multivariate measurement errors models. We propose the use of skew-normal/independent distributions to model the unobserved value of the covariates (latent variable) and symmetric normal/independent distributions for the random errors term, providing an appealing robust alternative to the usual symmetric process in multivariate measurement errors models. Among the distributions that belong to this class of distributions, we examine univariate and multivariate versions of the skew-normal, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.     

Stochastic models for fractal processes

This paper considers the situation where a stochastic process may display both long-range dependence (LRD) and intermittency. The existence of such a process is established in Anh et al. (1999). Existing works have commonly paid attention either to LRD or intermittency quite separately. This paper offers a convenient framework to study both effects simultaneously. A method is given to estimate and separate the two effects. The wavelet theory plays an essential role in this procedure. Numerical experiments on fractional Brownian motion and multiplicative cascade processes confirm the power of the method.     

The potential of integrated modelling in conservation biology: A case study of the black‐footed albatross (Phoebastria nigripes)

Conservation biology aims at assessing the status of a population, based on information which is often incomplete. Integrated population modelling based on state‐space models appears to be a powerful and relevant way of combining into a single likelihood several types of information such as capture‐recapture data and population surveys. In this paper, the authors describe the principles of integrated population modelling and they evaluate its performance for conservation biology based on a case study, that of the black‐footed albatross, a northern Pacific albatross species suspected to be impacted by longline fishing     

Adaptive weights smoothing with applications to image restoration

We propose a new method of nonparametric estimation which is based on locally constant smoothing with an adaptive choice of weights for every pair of data points. Some theoretical properties of the procedure are investigated. Then we demonstrate the performance of the method on some simulated univariate and bivariate examples and compare it with other nonparametric methods. Finally we discuss applications of this procedure to magnetic resonance and satellite imaging.     

“We're gonna get you through it”: The role of bonding social capital in the development of bridging social capital

Many programs that place low-income students of color in high-achieving college preparatory high schools seek to nurture bridging social capital, connections across class lines that provide leverage in the process of “getting ahead.” Bonding social capital, which focuses more on emotional support and “getting by,” is frequently characterized as less useful for social mobility. Drawing upon in-depth interviews with alumni from one such program, we challenge the notion of bridging and bonding social capital as discrete, countervailing forms of social capital, and demonstrate how the two may complement each other. Specifically, we find that bonding social capital served as a critical resource that students drew upon as they navigated their elite high schools in the face of racism and classism. In doing so, this bonding social capital ultimately facilitated the development of bridging social capital by encouraging student persistence at these institutions. Our findings support critiques of traditional accounts of social capital that devalue the capital possessed by marginalized communities and fuel deficit ideologies. Furthermore, they highlight the personal costs that youth may face in the pursuit of bridging capital, complicating the narrative of social mobility as an unmitigated good.     

Back for business: The link between foreign experience and entrepreneurship in Latvia

Research shows that return migrants have a higher propensity to set up an entrepreneurial activity or be self-employed compared to non-migrants. We take a multidisciplinary approach and empirically study the case of Latvia as a migration donor country to learn how re-migrants participate in entrepreneurship back at home. We are interested if return migrants can be seen as a vehicle for entrepreneurship development and if it is worth looking at them as agents of business growth and innovation. Not only we measure the fact of being entrepreneurial but also explore sources that contribute to the higher propensity, attitudes to creating own business venture, level of ambitions and population sentiment towards entrepreneurs. Based on a nationally representative adult population survey of 8000 observations, we find that early-stage entrepreneurial activity, established business ownership as well as intrapreneurship for return migrants exceed that of the non-migrant population. The self-perceived capabilities to start business is higher for those who have lived abroad, and fear of failure is lower. Return migrants also have better business networks and higher growth and export ambitions. Latvian return migrant entrepreneurship is not necessity driven but rather motivated by opportunities. Migration experience, length of stay aboard and capital accumulated abroad are found to be significant predictors of probability to become entrepreneur when controlled for socioeconomic and personal factors.