Interactive local bandwidth choice

A tool for user choice of the local bandwidth function for a kernel density estimate is developed using KDE, a graphical object-oriented package for interactive kernel density estimation written in LISP-STAT. The bandwidth function is a cubic spline, whose knots are manipulated by the user in one window, while the resulting estimate appears in another window. A real data illustration of this method raises concerns, because an extremely large family of estimates is available.

Flexible social organization and high incidence of drifting in the sweat bee, Halictus scabiosae.

The very diverse social systems of sweat bees make them interesting models to study social evolution. Here we focus on the dispersal behaviour and social organization of Halictus scabiosae, a common yet poorly known species of Europe. By combining field observations and genetic data, we show that females have multiple reproductive strategies, which generates a large diversity in the social structure of nests. A detailed microsatellite analysis of 60 nests revealed that 55% of the nests contained the offspring of a single female, whereas the rest had more complex social structures, with three clear cases of multiple females reproducing in the same nest and frequent occurrence of unrelated individuals. Drifting among nests was surprisingly common, as 16% of the 122 nests in the overall sample and 44% of the nests with complex social structure contained females that had genotypes consistent with being full-sisters of females sampled in other nests of the population. Drifters originated from nests with an above-average productivity and were unrelated to their nestmates, suggesting that drifting might be a strategy to avoid competition among related females. The sex-specific comparison of genetic differentiation indicated that dispersal was male-biased, which would reinforce local resource competition among females. The pattern of genetic differentiation among populations was consistent with a dynamic process of patch colonization and extinction, as expected from the unstable, anthropogenic habitat of this species. Overall, our data show that H. scabiosae varies greatly in dispersal behaviour and social organization. The surprisingly high frequency of drifters echoes recent findings in wasps and bees, calling for further investigation of the adaptive basis of drifting in the social insects.

The overhang hangover

We revisit the debt overhang question. We first use non-parametric techniques to isolate a panel of countries on the downward sloping section of a debt Laffer curve. In particular, overhang countries are ones where a threshold level of debt is reached in sample, beyond which (initial) debt ends up lowering (subsequent)growth. On average, significantly negative coefficients appear when debt face value reaches 60 percent of GDP or 200 percent of exports, and when its present value reaches 40 percent of GDP or 140 percent of exports. Second, we depart from reduced form growth regressions and perform direct tests of the theory on the thus selected sample of overhang countries. In the spirit of event studies, we ask whether, as overhang level of debt is reached: (i)investment falls precipitously as it should when it becomes optimal to default, (ii) economic policy deteriorates observably, as it should when debt contracts become unable to elicit effort on the part of the debtor, and (iii) the terms of borrowing worsen noticeably, as they should when it becomes optimal for creditors to pre-empt default and exact punitive interest rates. We find a systematic response of investment, particularly when property rights are weakly enforced, some worsening of the policy environment, and a fall in interest rates. This easing of borrowing conditions happens because lending by the private sector virtually disappears in overhang situations, and multilateral agencies step in with concessional rates. Thus, while debt relief is likely to improve economic policy (and especially investment) in overhang countries, it is doubtful that it would ease their terms of borrowing, or the burden of debt.

Variance reduction methods for simulation of densities on Wiener space

We develop a general error analysis framework for the Monte Carlo simulationof densities for functionals in Wiener space. We also study variancereduction methods with the help of Malliavin derivatives. For this, wegive some general heuristic principles which are applied to diffusionprocesses. A comparison with kernel density estimates is made.

Almost sure testability of classes of densities

Let a class $\F$ of densities be given. We draw an i.i.d.\ sample from a density $f$ which may or may not be in $\F$. After every $n$, one must make a guess whether $f \in \F$ or not. A class is almost surely testable if there exists such a testing sequence such that for any $f$, we make finitely many errors almost surely. In this paper, several results are given that allowone to decide whether a class is almost surely testable. For example, continuity and square integrability are not testable, but unimodality, log-concavity, and boundedness by a given constant are.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Peanut response to lime and molybdenum application in low pH soils

Liming acid soils is considered to assure the availability of Mo in crops. Additionally, in peanuts (Arachis hypogaea L.) the positive response to liming is associated to a better supply of Ca+2, Mo for the nitrogenase-complex activity, and other non-nitrogen fixing activities of the crop. This study was thus undertaken to assess the effect of lime, Mo, and the lime-Mo interaction on peanut crop, on an acid Ultisol at the Mococa Experimental Station, Instituto Agronômico, São Paulo State, Brazil, from 1987 to 1990. A randomized complete block design with four replications, in a 4 x 4 factorial arrangement, was used in the study. The factors included four lime rates (0, 2, 4, and 6 t ha-1) broadcast and incorporated into the soil, and Mo (0, 100, 200, and 300 g ha-1) as (NH4)2MoO4 applied as seed dressing. Lime was applied once at the beginning of the study while Mo was applied at every planting. Peanut seed cv 'tatu' was used. Significant increase in peanut kernel yield with liming was only evident in the absence of Mo, whereas the peanut response to Mo was observed in two out of the three harvests. A higher yield response (28 % increase) was found when Mo was applied without liming. Soil molybdenum availability, as indicated by plant leaf analysis, increased significantly when lime was applied. Molybdenum fertilization led to higher leaf N content, which in turn increased peanut yield in treatments with smaller lime doses.

One minute of grief: Emotional processing in short-term dynamic psychotherapy for adjustment disorder.

OBJECTIVE: Depth of emotional processing has shown to be related to outcome across approaches to psychotherapy. Moreover, a specific emotional sequence has been postulated and tested in several studies on experiential psychotherapy (Pascual-Leone & Greenberg, 2007). This process-outcome study aims at reproducing the sequential model of emotional processing in psychodynamic psychotherapy for adjustment disorder and linking these variables with ultimate therapeutic outcome. METHOD: In this study, 32 patients underwent short-term dynamic psychotherapy. On the basis of reliable clinical change statistics, a subgroup (n = 16) presented with good outcome and another subgroup (n = 16) had a poor outcome in the end of treatment. The strongest alliance session of each case was rated using the observer-rated system Classification of Affective Meaning States. Reliability coefficients for the measure were excellent (κ = .82). RESULTS: Using 1 min as the fine-grained unit of analysis, results showed that the experience of fundamentally adaptive grief was more common in the in-session process of patients with good outcome, compared with those with poor outcomes (χ2 = 6.56, p = .01, d = 1.23). This variable alone predicted 19% of the change in depressive symptoms as measured by the Beck Depression Inventory at the end of treatment. Moreover, sequences of the original model were supported and related to outcome. CONCLUSIONS: These results are discussed within the framework of the sequential model of emotional processing and its possible relevance for psychodynamic psychotherapy. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Semi-supervised remote sensing image classification with cluster kernels

A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Genetic differentiation for size at first reproduction through male versus female functions in the widespread Mediterranean tree Pinus pinaster.

BACKGROUND AND AIMS: The study of local adaptation in plant reproductive traits has received substantial attention in short-lived species, but studies conducted on forest trees are scarce. This lack of research on long-lived species represents an important gap in our knowledge, because inferences about selection on the reproduction and life history of short-lived species cannot necessarily be extrapolated to trees. This study considers whether the size for first reproduction is locally adapted across a broad geographical range of the Mediterranean conifer species Pinus pinaster. In particular, the study investigates whether this monoecious species varies genetically among populations in terms of whether individuals start to reproduce through their male function, their female function or both sexual functions simultaneously. Whether differences among populations could be attributed to local adaptation across a climatic gradient is then considered. METHODS: Male and female reproduction and growth were measured during early stages of sexual maturity of a P. pinaster common garden comprising 23 populations sampled across the species range. Generalized linear mixed models were used to assess genetic variability of early reproductive life-history traits. Environmental correlations with reproductive life-history traits were tested after controlling for neutral genetic structure provided by 12 nuclear simple sequence repeat markers. KEY RESULTS: Trees tended to reproduce first through their male function, at a size (height) that varied little among source populations. The transition to female reproduction was slower, showed higher levels of variability and was negatively correlated with vegetative growth traits. Several female reproductive traits were correlated with a gradient of growth conditions, even after accounting for neutral genetic structure, with populations from more unfavourable sites tending to commence female reproduction at a lower individual size. CONCLUSIONS: The study represents the first report of genetic variability among populations for differences in the threshold size for first reproduction between male and female sexual functions in a tree species. The relatively uniform size at which individuals begin reproducing through their male function probably represents the fact that pollen dispersal is also relatively invariant among sites. However, the genetic variability in the timing of female reproduction probably reflects environment-dependent costs of cone production. The results also suggest that early sex allocation in this species might evolve under constraints that do not apply to other conifers.

An axiomatization of the nucleolus of the assignment game

[cat] En el domini dels jocs bilaterals d’assignació, es presenta una axiomàtica del nucleolus com l´unica solució que compleix les propietats de consistència respecte del joc derivat definit per Owen (1992) i monotonia de les queixes dels sectors respecte de la seva cardinalitat. Com a conseqüència obtenim una caracterització geomètrica del nucleolus mitjançant una propietat de bisecció més forta que la que satisfan els punts del kernel (Maschler et al, 1979).

Symmetrically multilateral-bargained allocations in multi-sided assignment markets

[cat] Aquest treball tracta d’extendre la noció d’equilibri simètric de negociació bilateral introduït per Rochford (1983) a jocs d’assignació multilateral. Un pagament corresponent a un equilibri simètric de negociación multilateral (SMB) és una imputación del core que garanteix que qualsevol agent es troba en equilibri respecte a un procés de negociación entre tots els agents basat en allò que cadascun d’ells podria rebre -i fer servir com a amenaça- en un ’matching’ òptim diferent al que s’ha format. Es prova que, en el cas de jocs d’assignació multilaterals, el conjunt de SMB és sempre no buit i que, a diferència del cas bilateral, no sempre coincideix amb el kernel (Davis and Maschler, 1965). Finalment, responem una pregunta oberta per Rochford (1982) tot introduïnt un conjunt basat en la idea de kernel, que, conjuntament amb el core, ens permet caracteritzar el conjunt de SMB.

Flooded rice yield as affected by levels of water salinity in different stages of its cycle

Losses of productivity of flooded rice in the State of Rio Grande do Sul, Brazil, may occur in the Coastal Plains and in the Southern region due to the use of saline water from coastal rivers, ponds and the Laguna dos Patos lagoon, and the sensibility of the plants are variable according to its stage of development. The purpose of this research was to evaluate the production of rice grains and its components, spikelet sterility and the phenological development of rice at different levels of salinity in different periods of its cycle. The experiment was conducted in a greenhouse, in pots filled with 11 dm³ of an Albaqualf. The levels of salinity were 0.3 (control), 0.75, 1.5, 3.0 and 4.5 dS m-1 kept in the water layer by adding a salt solution of sodium chloride, except for the control, in different periods of rice development: tillering initiation to panicle initiation; tillering initiation to full flowering; tillering initiation to physiological maturity; panicle initiation to full flowering; panicle initiation to physiological maturity and full flowering to physiological maturity. The number of panicles per pot, the number of spikelets per panicle, the 1,000-kernel weight, the spikelet sterility, the grain yield and phenology were evaluated. All characteristics were negatively affected, in a quadratic manner, with increased salinity in all periods of rice development. Among the yield components evaluated, the one most closely related to grain yields of rice was the spikelet sterility.