Double ASN Minimax sampling plans by variables when the standard deviation is unknown

We deal with the double sampling plans by variables proposed by Bowker and Goode (Sampling Inspection by Variables, McGraw–Hill, New York, 1952) when the standard deviation is unknown. Using the procedure for the calculation of the OC given by Krumbholz and Rohr (Allg. Stat. Arch. 90:233–251, 2006), we present an optimization algorithm allowing to determine the ASN Minimax plan. This plan, among all double plans satisfying the classical two-point-condition on the OC, has the minimal ASN maximum.     

Marginal Changes in Random Parameters Ordered Response Models with Interaction Terms

Marginal changes of interacted variables and interaction terms in random parameters ordered response models are calculated incorrectly in econometric softwares. We derive the correct formulas for calculating these marginal changes. In our empirical example, we observe significant changes not only in the magnitude of the marginal effects but also in their standard errors, suggesting that the incorrect estimation of the marginal effects of these variables as is commonly practiced can render biased inferences on the findings.     

Estimation in an empirical bayes model for longitudinal and cross‐sectionally clustered binary data

Some studies generate data that can be grouped into clusters in more than one way. Consider for instance a smoking prevention study in which responses on smoking status are collected over several years in a cohort of students from a number of different schools. This yields longitudinal data, also cross‐sectionaliy clustered in schools. The authors present a model for analyzing binary data of this type, combining generalized estimating equations and estimation of random effects to address the longitudinal and cross‐sectional dependence, respectively. The estimation procedure for this model is discussed, as are the results of a simulation study used to investigate the properties of its estimates. An illustration using data from a smoking prevention trial is given.     

Choosing summary statistics by least angle regression for approximate Bayesian computation

Bayesian statistical inference relies on the posterior distribution. Depending on the model, the posterior can be more or less difficult to derive. In recent years, there has been a lot of interest in complex settings where the likelihood is analytically intractable. In such situations, approximate Bayesian computation (ABC) provides an attractive way of carrying out Bayesian inference. For obtaining reliable posterior estimates however, it is important to keep the approximation errors small in ABC. The choice of an appropriate set of summary statistics plays a crucial role in this effort. Here, we report the development of a new algorithm that is based on least angle regression for choosing summary statistics. In two population genetic examples, the performance of the new algorithm is better than a previously proposed approach that uses partial least squares.     

Optimization problems with color-induced budget constraints

In 1984, Gabow and Tarjan provided a very elegant and fast algorithm for the following problem: given a matroid defined on a red and blue colored ground set, determine a basis of minimum cost among those with k red elements, or decide that no such basis exists. In this paper, we investigate extensions of this problem from ordinary matroids to the more general notion of poset matroids which take precedence constraints on the ground set into account. We show that the problem on general poset matroids becomes -hard, already if the underlying partially ordered set (poset) consists of binary trees of height two. On the positive side, we present two algorithms: a pseudopolynomial one for integer polymatroids, i.e., the case where the poset consists of disjoint chains, and a polynomial algorithm for the problem to determine a minimum cost ideal of size l with k red elements, i.e., the uniform rank-l poset matroid, on series-parallel posets.     

Variable selection in discrete survival models including heterogeneity

Several variable selection procedures are available for continuous time-to-event data. However, if time is measured in a discrete way and therefore many ties occur models for continuous time are inadequate. We propose penalized likelihood methods that perform efficient variable selection in discrete survival modeling with explicit modeling of the heterogeneity in the population. The method is based on a combination of ridge and lasso type penalties that are tailored to the case of discrete survival. The performance is studied in simulation studies and an application to the birth of the first child.     

Contrasting strategies for tree species to cope with heat and dry conditions at urban sites

Street trees planted at tree pits with impermeable pavements are exposed to a high level of both, atmospheric and edaphic stress. For many species tree physiology, optimal growth, and consequently long-term vitality may be hampered under these harsh conditions. Therefore, maintaining the vitality and promoting the ecosystem services provided by urban trees, for example aesthetic values and microclimatic benefits, it is important to establish trees with a high tolerance to stressful urban environments. Measurements of leaf gas exchange, leaf water potential, leaf surface temperature and chlorophyll-fluorescence were used for identification of specific response of Corylus corluna L., Ginkgo biloba L., Liriodendron tulipifera L., and Tilia cordata Mill. ‘Greenspire’. The summer months in 2013 with a period of heat and drought over eight weeks only interrupted by two rainy days were appropriate to access tree’s strategies to cope with low water availability. During the measurement period, the influence of high temperatures, high values of vapor pressure deficit (VPD) and low soil water availability on stomatal conductance, water-use efficiency (WUE) and leaf water potential (Ψmin, Ψmax ) was highest for Liriodendron followed by Ginkgo. These species showed high reductions in WUE in case of higher air temperatures and high values of VPD. Results indicate an avoidance strategy under increasing heat and VPD. In contrast, Corylus and Tilia followed a tolerance strategy indicated by decreasing values of Ψmin and lower reductions of WUE. In conclusion, wide species-specific variation in response to high temperatures and high VPD indicates that substantial potential exists in the selection for dry and hot urban places.