Showing papers in "Technical reports in 2009"

Parameter estimation and validation of the terrestrial ecosystem model Biome-BGC using eddy-covariance flux measurements

Abstract: 4 INTRODUCTION 5 MODEL DESCRIPTION 7 MODEL UPDATES 10 MODELLING FOUR FOREST BIOME TYPES USING A PROCESS BASED ECOPHYSIOLOGICAL MODEL, BIOME-BGC: VALIDATION AND UNCERTAINTIES 12 OBJECTIVES 12 SITE CHARACTERISTICS AND METEOROLOGICAL DATA 13 TEMPERATE DECIDUOUS FOREST SITES 15 BOREAL CONIFEROUS FOREST SITES 17 BOREAL DECIDUOUS FOREST SITES 17 TEMPERATE CONIFEROUS FOREST SITES 18 NITROGEN DEPOSITION DATA 19 EDDY COVARIANCE FLUX DATA 19 MODEL PARAMETERISATION 20 MODEL SIMULATIONS AND VALIDATION 20 RESULTS AND DISCUSSION 22 MODEL PHENOLOGY 22 MODEL VALIDATION 24 PROBLEMATIC SITES 33 NORTH BOREAS 33 GUNNARSHOLT 36 CONCLUSIONS 36 PHENOLOGY 36 RESPIRATION 36 BOREAL SITES 37 MPI-BGC Tech Rep 16: Trusilova, Trembath, and Churkina 3 PARAMETER ESTIMATION FOR THE TERRESTRIAL ECOSYSTEM MODEL BIOMEBGC USING EDDY-COVARIANCE FLUX MEASUREMENTS 38 OVERVIEW OF PREVIOUS STUDIES 38 OBJECTIVES 39 MODEL PARAMETERISATION 39 MODEL SIMULATIONS 41 OBSERVATIONAL DATA 43 UNCERTAINTIES 43 NONLINEAR INVERSION 44 MISFIT FUNCTION 45 THE UNCERTAINTY OF MODEL OUTPUT 46 ONE ITERATION OF THE OPTIMISATION 47 CONSTRAINTS ON THE MODEL OUTPUT 49 RESULTS AND DISCUSSION 49 UNCERTAINTY IN CARBON FLUXES 50 OPTIMISED PARAMETER VALUES 52 TESTING OPTIMISED PARAMETERS 55 REDUCTION OF FLUX UNCERTAINTY WITH OPTIMISED PARAMETERS 56 CONCLUSIONS 57 ACKNOWLEDGMENTS 59 REFERENCES 60 MPI-BGC Tech Rep 16: Trusilova, Trembath, and Churkina 4

Frequency estimation by DFT interpolation: a comparison of methods

Abstract: This article comments on a frequency estimator which was proposed by [6] and shows empirically that it exhibits a much larger mean squared error than a well known frequency estimator by [8]. It is demonstrated that by using a heuristical adjustment [2] the performance can be greatly improved. Furthermore, references to two modern techniques are given, which both nearly attain the Cramer-Rao bound for this estimation problem.

Characterisation of the tuna purse seine fishery in Papua New Guinea.

Abstract: Complimentary hard copies are available to developing-country researchers and institutions involved in agriculture from ACIAR’s operating area. For a free copy, fill out the request form, available online or by contacting ACIAR’s Communications Unit, comms@aciar.gov.au The Australian Centre for International Agricultural Research (ACIAR) is pleased to announce the publication of Characterisation of the tuna purse seine fishery in Papua New Guinea.

Soil fertility in sweetpotato-based cropping systems in the highlands of Papua New Guinea

Abstract: The main outputs anticipated include enchanced knowledge of key water-nutrient dynamics in relation to key soil management techniques and a suite of improved and practical soil management options in sweet potatoes.

Labor Force Status Dynamics in the German Labor Market - Individual Heterogeneity and Cyclical Sensitivity

Abstract: The aggregate average unemployment rate in a given country is essentially the result of individual workers' transitions between the three core labor force states, employment, unemployment, and inactivity. The dynamics of these transitions depend both, on individual duration in a particular state and the transition probabilities between states. Individual transitions, in turn, depend on observable and unobserved factors. Simultaneously, person-specific dynamics may be influenced by swings of the business cycle. This paper analyzes these labor force status dynamics for the East and West German labor market, separately using comprehensive data on monthly transitions from the SOEP. The results show that the experience of high unemployment rates is more sensitive to cyclical behavior for certain demographic groups, specifically unskilled and young workers. Heterogeneity in unemployment and transition rates differ between East and West Germany, as well as between the sexes. In East Germany, all demographic cells are almost entirely detached from the cycle. Women are less influenced by the cycle in their re-employment rate from unemployment to employment.

Constructing irregular histograms by penalized likelihood

Abstract: We propose a fully automatic procedure for the construction of irregular histograms. For a given number of bins, the maximum likelihood histogram is known to be the result of a dynamic programming algorithm. To choose the number of bins, we propose two different penalties motivated by recent work in model selection by Castellan [6] and Massart [26]. We give a complete description of the algorithm and a proper tuning of the penalties. Finally, we compare our procedure to other existing proposals for a wide range of different densities and sample sizes.

The Importance of Two-Sided Heterogeneity for the Cyclicality of Labour Market Dynamics

Abstract: Using two data sets derived from German administrative data, including a linked employer-employee data set, we investigate the cyclicality of worker and job flows.The analysis stresses the importance of two-sided labour market heterogeneity in this context, taking into account both observed and unobserved characteristics.We find that small firms hire mainly unemployed workers, and that they do so at the beginning of an economic expansion. Later on in the expansion, hirings more frequently result from direct job-to-job transitions, with employed workers moving to larger firms. Contrary to our expectations, workers moving to larger firms do not experience significantly larger wage gains than workers moving to smaller establishments. Furthermore, our econometric analysis shows that the interaction of unobserved heterogeneities on the two sides of the labour market plays a more important role for employed job seekers than for the unemployed.

Kernelized design of experiments

Abstract: This paper describes an approach for selecting instances in regression problems in the cases where observations x are readily available, but obtaining labels y is hard. Given a database of observations, an algorithm inspired by statistical design of experiments and kernel methods is presented that selects a set of k instances to be chosen in order to maximize the prediction performance of a support vector machine. It is shown that the algorithm significantly outperforms related approaches on a number of real-world datasets.

Robustness of optimal designs for the Michaelis-Menten model under a variation of criteria

Abstract: The Michaelis-Menten model has and continues to be one of the most widely used models in many diverse fields. In the biomedical sciences, the model continues to be ubiquitous in biochemistry, enzyme kinetics studies, nutrition science and in the pharmaceutical sciences. Despite its wide ranging applications across disciplines, design issues for this model are given short shrift. This paper focuses on design issues and provides a variety of optimal designs of this model. In addition, we evaluate robustness properties of the optimal designs under a variation in optimality criteria. To facilitate use of optimal design ideas in practice, we design a web site for generating and comparing dfferent types of tailor-made optimal designs and user-supplied designs for the Michaelis-Menten and related models.

On the Security of End-to-End Network Measurements; ; Technical Reports;

Abstract: End-to-end network measurement tools are gaining increased importance in many Internet services. These tools were designed, however, without prior security consideration which, given the current adversarial Internet, renders their extracted network estimates questionable. In this paper, we highlight the major security vulnerabilities of existing end-to-end measurement tools and we sketch possible research directions to counter these threats. We further argue that finding “fullfledged” solutions for these challenges might require a serious re-design of the current Internet.

A Token-Ring for the TRM

Abstract: With the design of the Token-Ring for the TRM (Tiny Register Machine) I pursued mainly two aims. The first is to design a network connecting several TRM cores. The second is to go for a design that is as simple as possible, considering that the TRM project is oriented towards educational hard- and software. Featuring a ring architecture, it provides a welcome alternative to the already existing bus architecture implemented by Ling Liu, allowing to compare complexity and performance.

D-optimal plans for variable selection in data bases

Abstract: This paper is based on an article of Pumplun et al. (2005a) that investigates the use of Design of Experiments in data bases in order to select variables that are relevant for classification in situations where a sufficient number of measurements of the explanatory variables is available, but measuring the class label is hard, e. g. expensive or time-consuming. Pumplun et al. searched for D-optimal designs in existing data sets by means of a genetic algorithm and assessed variable importance based on the found plans. If the design matrix is standardized these D-optimal plans are almost orthogonal and the explanatory variables are nearly uncorrelated. Thus Pumplun et al. expected that their importance for discrimination can be judged independently of each other. In a simulation study Pumplun et al. applied this approach in combination with five classification methods to eight data sets and the obtained error rates were compared with those resulting from variable selection on the basis of the complete data sets. Based on the D-optimal plans in some cases considerably lower error rates were achieved. Although Pumplun et al. (2005a) obtained some promising results, it was not clear for different reasons if D-optimality actually is beneficial for variable selection. For example, D-efficiency and orthogonality of the resulting plans were not investigated and a comparison with variable selection based on random samples of observations of the same size as the D-optimal plans was missing. In this paper we extend the simulation study of Pumplun et al. (2005a) in order to verify their results and as basis for further research in this field. Moreover, in Pumplun et al. D-optimal plans are only used for data preprocessing, that is variable selection. The classification models are estimated on the whole data set in order to assess the effects of D-optimality on variable selection separately. Since the number of measurements of the class label in fact is limited one would normally employ the same observations that were used for variable selection for learning, too. For this reason in our simulation study the appropriateness of D-optimal plans for training classification methods is additionally investigated. It turned out that in general in terms of the error rate there is no difference between variable selection on the basis of D-optimal plans and variable selection on random samples. However, for training of linear classification methods D-optimal plans seem to be beneficial.

Biases in the measurement of labour market dynamics

Abstract: This paper analyses worker transitions on the German labour market derived from different data sources. These include the two German micro data sets which provide high-frequency observations on workers' employment and unemployment histories: the German Socioeconomic Panel (SOEP) and the IAB Employment Subsample (IABS). This exercise thus yields a comprehensive overview of German labour market dynamics. Furthermore, it highlights the differences between the results obtained from a retrospective survey, the SOEP, and a process-induced administrative data set, the IABS. In particular, our analysis shows which groups of the labour market are particularly affected by measurement error. We also show which role measurement issues play when establishing the stylised facts about the cyclicality of labour market dynamics.

Deriving a statistical model for the prediction of spiralling in BTA deep hole drilling from a physical model

Abstract: One serious problem in deep-hole drilling is the occurrence of a dynamic disturbances called spiralling. A common explanation for the occurrence of spiralling is the coincidence of time varying bending eigenfrequencies of the tool with multiples of the spindle rotation frequency. We propose a statistical model for the estimation of the eigenfrequencies derived from a physical model. The major advantage of the statistical model is that it allows to estimate the parameters of the physical model directly from data measured during the process. This represents an efficient way of detecting situations in which spiralling is likely and of deriving countermeasures.