**Eldorado**

Resources for and from Research, Teaching and Studying

### Recent Submissions

We introduce generalized sign tests based on K-sign depth, shortly denoted by K-depth. These so-called K-depth tests are motivated by simplicial regression depth. Since they depend only on the signs of the residuals, these test statistics are easy to comprehend and outlier robust. We show that the K-depth test with K = 2 is equivalent to the classical sign test so that K-depth tests with K > 2 are generalizations of the classical sign test. Since the K-depth test with K = 2 is equivalen...

I propose a generalized method of moments estimator for structural vector autoregressions with non-Gaussian shocks. The shocks are identified by exploiting information contained in higher moments of the data. Extending the standard identification approach, which relies on the shocks' covariance, to the shocks' coskewness and cokurtosis allows to identify the simultaneous interaction without any further restrictions. I analyze the estimator's performance depending on the co-moments used ...

In this paper we investigate the problem of designing experiments for series estimators in nonparametric regression models with correlated observations. We use projection based estimators to derive an explicit solution of the best linear oracle estimator in the continuous time model for all Markovian-type error processes. These solutions are then used to construct estimators, which can be calculated from the available data along with their corresponding optimal design points. Our results are ...

We propose a goodness-of-fit test for the distribution of errors from a multivariate indirect regression model. The test statistic is based on the Khmaladze transformation of the empirical process of standardized residuals. This goodness-of-fit test is consistent at the root-n rate of convergence, and the test can maintain power against local alternatives converging to the null at a root-n rate.

Due to the surge of data storage techniques, the need for the development of appropri-ate techniques to identify patterns and to extract knowledge from the resulting enormous data sets, which can be viewed as collections of dependent functional data, is of increasing interest in many scientific areas. We develop a similarity measure for spectral density oper-ators of a collection of functional time series, which is based on the aggregation of Hilbert-Schmidt differences of the individual time...

In this paper, aliasing effects are investigated for random ﬁelds deﬁned on the d-dimensional sphere Sd, and reconstructed from discrete samples. First, we introduce the concept of an aliasing function on Sd. The aliasing function allows to identify explicitly the aliases of a given harmonic coefficient in the Fourier decomposition. Then, we exploit this tool to establish the aliases of the harmonic coefficients approximated by means of the quadrature procedure named spherical uniform samp...

Drawing on a consumer search model and a unique panel data set of daily fuel prices covering over 5,000 fuel stations in Germany, this paper documents a change in the price setting behavior of retail gas stations following the introduction of a legally mandated on-line price portal. Prior to the introduction of the portal in 2013, positive asymmetry is found on the basis of error correction models, with prices following the “rockets and feathers” pattern documented in many commodity mark...

The lifetime of diamond impregnated tools for core drilling of concrete is studied via the lifetimes of the single diamonds on the tool. Thereby, the number of visible and active diamonds on the tool surface is determined by microscopical inspections of the tool at given points in time. This leads to interval-censored lifetime data if only the diamonds visible at the beginning are considered. If also the lifetimes of diamonds appearing during the drilling process are included then the l...

For estimating the remaining lifetime of old prestressed concrete bridges, a monitoring of crack widths can be used. However, the time series of crack widths show a strong variation mainly caused by temperature and traffic. Additionally, sequences with extreme volatility appear where the cause is unknown. They are called anomalous sequences in the following.We present and compare four methods which aim to detect these anomalous sequences in the time series. Volatilities caused by traffi...

In this paper we study the theoretical properties of the simultaneous multiscale change point estimator (SMUCE) proposed by Frick et al. (2014) in regression models with dependent error processes. Empirical studies show that in this case the change point estimate is inconsistent, but it is not known if alternatives suggested in the literature for correlated data are consistent. We propose a modification of SMUCE scaling the basic statistic by the long run variance of the error process, w...

This paper considers group-mean fully modified OLS estimation for a panel of cointegrating polynomial regressions, i. e., regressions that include an integrated process and its powers as explanatory variables. The stationary errors are allowed to be serially correlated, the regressor to be endogenous and { as usual in the nonstationary panel literature { we include individual specific fixed effects. We consider a fixed cross-section dimension, asymptotics in the time dimension only and s...

We model an overdispersed count as a dependent measurement, by means of the Negative Binomial distribution. We consider quantitative regressors that are ﬁxed by design. The expectation of the dependent variable is assumed to be a known function of a linear combination involving regressors and their coefficients. In the NB1-parametrization of the negative binomial distribution, the variance is a linear function of the expectation, inﬂated by the dispersion parameter, and not a generalized...

We introduce a set of new Value-at-Risk independence backtests by establishing a connection between the independence property of Value-at-Risk forecasts and the extremal index, a general measure of extremal clustering of stationary sequences. We introduce a sequence of relative excess returns whose extremal index has to be estimated. We compare our backtest to both popular and recent competitors using Monte-Carlo simulations and find considerable power in many scenarios. In an applied s...

One way to reduce emissions from the consumption of electricity is switching to green electricity suppliers. This paper identifies the determinants of adopting green electricity and the effect on electricity consumption, using panel data on more than 9,000 households. To control for potential self-selection into green electricity tariffs, an endogenous dummy treatment effects model is estimated. The results suggest that wealthier and better-educated households are more likely to adopt gr...

Feature selection is an important task in machine learning, reducing dimensionality of learning problems by selecting few relevant features without losing too much information. Focusing on smaller sets of features, we can learn simpler models from data that are easier to understand and to apply. In fact, simpler models are more robust to input noise and outliers, often leading to better prediction performance than the models trained in higher dimensions with all features. We implement several...

We present our ongoing collaborative work on EnDroid, an energy-efficient GPS-based positioning system for the Android Operating System. EnDroid is based on the EnTracked positioning system, developed at the University of Aarhus, Denmark. We describe the current prototypical state of our implementation and present our experiences and conclusions from preliminarily evaluating EnDroid on the Google Nexus One Smartphone. Although the preliminary results seem to sup- port the approach, there are...

This Report describes the technical background and usage of the GraphMod plug-in for RapidMiner. The plug-in enables RapidMiner to load factor graphs and interpret Label and Attributes which are contained in an Example as assignments to random variables. A set of examples which belong to the same Batch is treated as assignment to a whole factor graph. New operators allow the estimation of factor weights, the computation of the single-node marginal probability functions and the computation of ...

Empirical analysis of statistical algorithms often demands time-consuming experiments which are best performed on high performance computing clusters. We present two R packages which greatly simplify working in batch computing environments. The package BatchJobs implements the basic objects and procedures to control a batch cluster within R. It is structured around cluster versions of the well-known higher order functions Map, Reduce and Filter from functional programming. An important featur...

### Collections in this community

#### Sonderforschungsbereich (SFB) 475 [595]

Reduction of Complexity for Multivariate Data Structures

#### Sonderforschungsbereich (SFB) 531 [249]

Design und Management komplexer technischer Prozesse und Systeme mit Methoden der Computational Intelligence

#### Sonderforschungsbereich (SFB) 559 [64]

Modellierung grosser Netze in der Logistik

#### Sonderforschungsbereich (SFB) 823 [486]

Nichtlineare dynamische Modelle in Wirtschaft und Technik

#### Sonderforschungsbereich (SFB) 876 [90]

Verfügbarkeit von Information durch Analyse unter Ressourcenbeschränkung

#### Sonderforschungsbereich (SFB) Transregio 10 [0]

Integration von Umformen, Trennen und Fügen für die flexible Fertigung von leichten Tragwerkstrukturen