Un análisis comparativo del papel del bucle fonológico versus la agenda visoespacial en el cálculo en niños de 7-8 años = A comparative analysis of the phonological loop versus the visuo-spatial sketchpad in mental arithmetic tasks in 7-8 y.o. children

En esta investigación se ha estudiado la relación entre dos subsistemas de la memoria de trabajo (buclefonológico y agenda viso-espacial) y el rendimiento en cálculo con una muestra de 94 niños españolesde 7-8 años. Hemos administrado dos pruebas de cálculo diseñadas para este estudio y seis medidassimples de memoria de trabajo (de contenido verbal, numérico y espacial) de la «Batería de Testsde Memoria de Treball» de Pickering, Baqués y Gathercole (1999), y dos pruebas visuales complementarias.Los resultados muestran una correlación importante entre las medidas de contenido verbaly numérico y el rendimiento en cálculo. En cambio, no hemos encontrado ninguna relación con las medidasespaciales. Se concluye, por lo tanto, que en escolares españoles existe una relación importanteentre el bucle fonológico y el rendimiento en tareas de cálculo. En cambio, el rol de la agenda viso-espaciales nulo

Analysis of laboratory intercomparison data: a matter of independence

When laboratory intercomparison exercises are conducted, there is no a priori dependence of the concentration of a certain compound determined in one laboratory to that determined by another(s). The same applies when comparing different methodologies. A existing data set of total mercury readings in fish muscle samples involved in a Brazilian intercomparison exercise was used to show that correlation analysis is the most effective statistical tool in this kind of experiments. Problems associated with alternative analytical tools such as mean or paired 't'-test comparison and regression analysis are discussed.

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

Compositional data analysis of vote shares in the 2001 Australian Federal election

First application of compositional data analysis techniques to Australian election data

Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

The single principle of compositional data analysis, continuing fallacies, confusionsand misunderstandings and some suggested remedies

In any discipline, where uncertainty and variability are present, it is important to haveprinciples which are accepted as inviolate and which should therefore drive statisticalmodelling, statistical analysis of data and any inferences from such an analysis.Despite the fact that two such principles have existed over the last two decades andfrom these a sensible, meaningful methodology has been developed for the statisticalanalysis of compositional data, the application of inappropriate and/or meaninglessmethods persists in many areas of application. This paper identifies at least tencommon fallacies and confusions in compositional data analysis with illustrativeexamples and provides readers with necessary, and hopefully sufficient, arguments topersuade the culprits why and how they should amend their ways

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

A panel data analysis of FDI and informal labor markets

The objective of this paper is to examine whether informal labor markets affect the flows of Foreign Direct Investment (FDI), and also whether this effect is similar in developed and developing countries. With this aim, different public data sources, such as the World Bank (WB), and the United Nations Conference on Trade and Development (UNCTAD) are used, and panel econometric models are estimated for a sample of 65 countries over a 14 year period (1996-2009). In addition, this paper uses a dynamic model as an extension of the analysis to establish whether such an effect exists and what its indicators and significance may be.

Economic Geographical Analysis of The Finnish Paper Industry

The purpose of this academic economic geographical dissertation is to study and describe how competitiveness in the Finnish paper industry has developed during 2001–2008. During these years, the Finnish paper industry has faced economically challenging times. This dissertation attempts to fill the existing gap between theoretical and empirical discussions concerning economic geographical issues in the paper industry. The main research questions are: How have the supply chain costs and margins developed during 2001–2008? How do sales prices, transportation, and fixed and variable costs correlate with gross margins in a spatial context? The research object for this case study is a typical large Finnish paper mill that exports over 90 % of its production. The economic longitudinal research data were obtained from the case mill’s controlled economic system and, correlation (R2) analysis was used as the main research method. The time series data cover monthly economic and manufacturing observations from the mill from 2001 to 2008. The study reveals the development of prices, costs and transportation in the case mill, and it shows how economic variables correlate with the paper mills’ gross margins in various markets in Europe. The research methods of economic geography offer perspectives that pay attention to the spatial (market) heterogeneity. This type of research has been quite scarce in the research tradition of Finnish economic geography and supply chain management. This case study gives new insight into the research tradition of Finnish economic geography and supply chain management and its applications. As a concrete empirical result, this dissertation states that the competitive advantages of the Finnish paper industry were significantly weakened during 2001–2008 by low paper prices, costly manufacturing and expensive transportation. Statistical analysis expose that, in several important markets, transport costs lower gross margins as much as decreasing paper prices, which was a new finding. Paper companies should continuously pay attention to lowering manufacturing and transporting costs to achieve more profitable economic performance. The location of a mill being far from markets clearly has an economic impact on paper manufacturing, as paper demand is decreasing and oversupply is pressuring paper prices down. Therefore, market and economic forecasting in the paper industry is advantageous at the country and product levels while simultaneously taking into account the economic geographically specific dimensions.

Spatial variability of air dry bulb temperature and black globe humidity index in a broiler house during the heating phase

The air dry-bulb temperature (t db),as well as the black globe humidity index (BGHI), exert great influence on the development of broiler chickens during their heating phase. Therefore, the aim of this study was to analyze the structure and the magnitude of the t db and BGHI spatial variability, using geostatistics tools such as semivariogram analysis and also producing kriging maps. The experiment was conducted in the west mesoregion of the states of Minas Gerais in 2010, in a commercial broiler house with heating system consisting of two furnaces that heat the air indirectly, in the firsts 14 days of the birds' life. The data were registered at intervals of five minutes in the period from 8 a.m. to 10 a.m. The variables were evaluated by variograms fitted by residual maximum likelihood (REML) testing the Spherical and Exponential models. Kriging maps were generated based on the best model used to fit the variogram. It was possible to characterize the variability of the t db and BGHI, which allowed observing the spatial dependence by using geostatistics techniques. In addition, the use of geostatistics and distribution maps made possible to identify problems in the heating system in regions inside the broiler house that may harm the development of chicks.

Spatial variability of mechanical resistance to penetration evaluated with mobile unit on haplic vertisol cultivated with mango

Since the advent of mechanized farming and intensive use of agricultural machinery and implements on the properties, the soil began to receive greater load of machinery traffic, which can cause increased soil compaction. The aim of this study was to evaluate the spatial variability of soil mechanical resistance to penetration (RP) in the layers of 0.00-0.10, 0.10-0.20, 0.20-0.30 and 0.30-0.40m, using geostatistics in an area cultivated with mango in Haplic Vertisol of the northeastern semi-arid, with mobile unit equipped with electronic penetrometer. The RP data was collected in 56 points from an area of 3 ha, and random soil samples were collected to determine the soil moisture and texture. For RP data analysis we used descriptive statistics and geostatistics. The soil mechanical resistance to penetration presented increased variability, with adjustment of the spherical and exponential semivariograms in the layers. We found that 42% of the area in the layer of 0.10-0.20m showed RP values above 2.70 MPa. Maximum values of RP were found in the layer of 0.19-0.27m, predominantly in 56% of the area.

Identification, assessment and ordering of concepts for agro-energy planning and possibilities of spatial analysis

ABSTRACT The present study aims to present the main concepts of the sugarcane straw to energy planning. Throughout the study, the subject is contextualized highlighting broader aspects of sustainability, which is considered the main driver towards agro-energy modernization. Concerning sugarcane straw, we first evaluated its availability regarding technical and economic aspects, and then it summarized the straw production chain for energy supply purposes. As a proposal to support agro-energy planning, it is presented some spatial tools that have been barely used in the Brazilian energy planning context so far. Therefore, working on straw to electricity associated with supply chain basis, we developed a conceptual model to spatially assess this bioenergy system. Using the model proposed, it is described the whole supply chain at state level, which accounted the potential of a single mill to explore straw, as well as main costs associated with straw acquisition, investments on the straw recovery routes and electricity transmission. Bearing these concepts in mind, it is fully believed that spatial analysis can bring important information for agro-energy action plans.

Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

On Bayesian predictive modeling : with applications on the analysis of chromatography data in forensic investigations

Med prediktion avses att man skattar det framtida värdet på en observerbar storhet. Kännetecknande för det bayesianska paradigmet är att osäkerhet gällande okända storheter uttrycks i form av sannolikheter. En bayesiansk prediktiv modell är således en sannolikhetsfördelning över de möjliga värden som en observerbar, men ännu inte observerad storhet kan anta. I de artiklar som ingår i avhandlingen utvecklas metoder, vilka bl.a. tillämpas i analys av kromatografiska data i brottsutredningar. Med undantag för den första artikeln, bygger samtliga metoder på bayesiansk prediktiv modellering. I artiklarna betraktas i huvudsak tre olika typer av problem relaterade till kromatografiska data: kvantifiering, parvis matchning och klustring. I den första artikeln utvecklas en icke-parametrisk modell för mätfel av kromatografiska analyser av alkoholhalt i blodet. I den andra artikeln utvecklas en prediktiv inferensmetod för jämförelse av två stickprov. Metoden tillämpas i den tredje artik eln för jämförelse av oljeprover i syfte att kunna identifiera den förorenande källan i samband med oljeutsläpp. I den fjärde artikeln härleds en prediktiv modell för klustring av data av blandad diskret och kontinuerlig typ, vilken bl.a. tillämpas i klassificering av amfetaminprover med avseende på produktionsomgångar.

The Use of Data Envelopment Analysis as Equity Portfolio Selection Criterion in the Finnish Stock Market

This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.