CTIT technical reports series最新文献

{"title":"Constrained optimal discriminating designs for Fourier regression models","authors":"Stefanie Biedermann, H. Dette, P. Hoffmann","doi":"10.17877/DE290R-3087","DOIUrl":"https://doi.org/10.17877/DE290R-3087","url":null,"abstract":"In this article, the problem of constructing efficient discriminating designs in a Fourier regression model is considered. We propose designs which maximize the efficiency for the estimation of the coefficient corresponding to the highest frequency subject to the constraints that the coefficients of the lower frequencies are estimated with at least some given efficiency. A complete solution is presented using the theory of canonical moments, and for the special case of equal constraints the optimal designs can be found analytically.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"148 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73451832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Similarity measures for clustering SNP and epidemiological data","authors":"S. Selinski","doi":"10.17877/DE290R-15898","DOIUrl":"https://doi.org/10.17877/DE290R-15898","url":null,"abstract":"The issue of suitable similarity measures for a joint consideration of so called SNP data and epidemiological variables arises from the GENICA (Interdisciplinary Study Group on Gene Environment Interaction and Breast Cancer in Germany) casecontrol study of sporadic breast cancer. The GENICA study aims to investigate the influence and interaction of single nucleotide polymorphic (SNP) loci and exogenous risk factors. A single nucleotide polymorphism is a point mutation that is present in at least 1 % of a population. SNPs are the most common form of human genetic variations. In particular, we consider 43 SNP loci in genes involved in the metabolism of hormones, xenobiotics and drugs as well as in the repair of DNA. Assuming that these single nucleotide changes may lead, for instance, to altered enzymes or to a reduced or enhanced amount of the original enzymes – with each alteration alone having minor effects – the aim is to detect combinations of SNPs that under certain environmental conditions increase the risk of sporadic breast cancer. The search for patterns in the present data set may be performed by a variety of clustering and classification approaches. I consider here the problem of suitable measures of proximity of two variables or subjects as an indispensable basis for a further cluster analysis. In the present data situation these measures have to be able to handle different numbers and meaning of categories of nominal scaled data as well as data of different scales. Generally, clustering approaches are a useful tool to detect structures and to generate hypothesis about potential relationships in complex data situations. Searching for patterns in the data there are two possible objectives: the identification of groups of similar objects or subjects or the identification of groups of similar variables within the whole or within subpopulations. The different objectives imply different requirements on the measures of similarity. Comparing the individual genetic profiles as well as comparing the genetic information across subpopulations I discuss possible choices of similarity measures suitable for genetic and epidemiological data, in particular, measures based on the ÷2-statistic, Flexible Matching Coefficients and combinations of similarity measures.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88678893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balanced Growth and Empirical Proxies of the Consumption-Wealth Ratio","authors":"Mathias Hoffmann","doi":"10.17877/DE290R-839","DOIUrl":"https://doi.org/10.17877/DE290R-839","url":null,"abstract":"Empirical proxies of the aggregate consumption-wealth ratio in terms of a cointegrating relationship between consumption (c), asset wealth (a) and labour income (y), commonly referred to as cay-residuals, play an important role in recent empirical research in macroeconomics and finance. This paper shows that the balanced-growth assumption made in deriving cay implies a second cointegrating relationship between the three variables; the three great ratios c - a, c - y and a - y should all be individually stationary In U.S. data I find evidence for this second cointegrating relationship once I control for deterministic trends and a structural break. The fact that cay is a linear combination of two stationary great ratios has a number of important implications. First, without additional identifying restrictions, the residual from a cointegrating regression can no longer be interpreted as an approximation of the aggregate consumption-wealth ratio. I discuss an identifying assumption that may still allow to do so. Secondly, predictive regressions of asset prices on a combination of two stationary great ratios, must do at least as well as regressions on cay alone. Still, cay proves remarkably robust as an indicator of aggregate asset price cycles. The findings here also inform a recent debate about the role of look-ahead bias in cay: in order to identify transitory components in asset prices, households do not need to identify the parameters of the cay-relation at all.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89319294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing Associations in Multivariate Binary Time Series","authors":"R. Fried, S. Kuhls, Isabel Molina","doi":"10.17877/DE290R-14323","DOIUrl":"https://doi.org/10.17877/DE290R-14323","url":null,"abstract":"We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the contemporaneous associations are misspecified. Particularly, we can detect and test Granger non-causalities since they correspond to zero parameter values.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79121477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling and Understanding of Chatter","authors":"P. Wolfrum, A. Gepperth, Yulia Sandamirskaya, O. Webber, N. Raabe","doi":"10.17877/DE290R-14225","DOIUrl":"https://doi.org/10.17877/DE290R-14225","url":null,"abstract":"Recent analysis in chatter modelling of BTA deep-hole drilling consisted in phenomenological modelisation of relationships between the observed time series and appearance of chatter during the process. Using the newly developed MEWMA control chart [4, 5], it has even been possible to predict the occurence of chatter about 30 to 50 mm in advance (i.e. up to one minute before the chatter starts). Unfortunately, no relationships between the machine and model parameters have been detected. Therefore, in this paper a physical model of the boring bar is taken into account. Simulation studies of the regenerative process are performed. These simulated time series show the same characteristics as the data recorded during the drilling process and thus support the validity of our model. By running such simulations, we intend to find strategies for chatter prevention in future work.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86014400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of spiralling in BTA deep-­hole drilling - estimating the system's eigenfrequencies","authors":"G. Szepannek, N. Raabe, O. Webber, C. Weihs","doi":"10.17877/DE290R-15668","DOIUrl":"https://doi.org/10.17877/DE290R-15668","url":null,"abstract":"One serious problem in deep-hole drilling is the formation of a dynamic disturbance called spiralling which causes holes with several lobes. Since such lobes are a severe impairment of the bore hole quality the formation of spiralling has to be prevented. Gessesse et al. [2] explain spiralling by the coincidence of bending modes and multiples of the rotation frequency. They derive this from an elaborate finite elements model of the process. In online measurements we detected slowly changing frequency patterns similar to those calculated by Gessesse et al. We therefore propose a method to estimate the parameters determining the change of frequencies over time from spectrogram data. This significantly simplifies the explanation of spiralling for practical applications compared to finite elements models which have to be correctly modified for each machine and tool assembly. It turns out that this simpler model achieves to explain the observed frequency patterns quite well. We use this for estimating the variation of the frequencies as good as possible. This opens up the opportunity to prevent spiralling by e.g. changing the rotary frequency.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88654933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long range financial data and model choice","authors":"P. L. Davies","doi":"10.17877/DE290R-14162","DOIUrl":"https://doi.org/10.17877/DE290R-14162","url":null,"abstract":"Long range financial data as typified by the daily returns of the Standard and Poor's index exhibit common features such as heavy tails, long range memory of the absolute values and clustering of periods of high and low volatility. These and other features are often referred to as stylized facts and parametric models for such data are required to reproduce them in some sense. Typically this is done by simulating some data sets under the model and demonstrating that the simulations also exhibits the stylized facts. Nevertheless when the parameters of such models are to be estimated recourse is very often taken to likelihood either in the form of maximum likelihood or Bayes. In this paper we expound a method of determining parameter values which depends solely on the ability of the model to reproduce the relevant features of the data set. We introduce a new measure of the volatility of the volatility and show how it can be combined with the distribution of the returns and the autocorrelation of the absolute returns to determine parameter values. We also give a parametric model for such data and show that it can reproduce the required features.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89880917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response Surface Methodology for Optimizing Hyper Parameters","authors":"C. Weihs, Karsten Luebke, I. Czogiel","doi":"10.17877/DE290R-14252","DOIUrl":"https://doi.org/10.17877/DE290R-14252","url":null,"abstract":"The performance of an algorithm often largely depends on some hyper parameter which should be optimized before its usage. Since most conventional optimization methods suffer from some drawbacks, we developed an alternative way to find the best hyper parameter values. Contrary to the well known procedures, the new optimization algorithm is based on statistical methods since it uses a combination of Linear Mixed Effect Models and Response Surface Methodology techniques. In particular, the Method of Steepest Ascent which is well known for the case of an Ordinary Least Squares setting and a linear response surface has been generalized to be applicable for repeated measurements situations and for response surfaces of order o ?U 2.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"215 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79602384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exact optimal designs for weighted least squares analysis with correlated errors","authors":"H. Dette, J. Kunert, A. Pepelyshev","doi":"10.17877/DE290R-1944","DOIUrl":"https://doi.org/10.17877/DE290R-1944","url":null,"abstract":"In the common linear and quadratic regression model with an autoregressive error structure exact D-optimal designs for weighted least squares analysis are determined. It is demonstrated that for highly correlated observations the D-optimal design is close to the equally spaced design. Moreover, the equally spaced design is usually very efficient, even for moderate sizes of the correlation, while the D-optimal design obtained under the assumptions of independent observations yields a substantial loss in efficiency. We also consider the problem of designing experiments for weighted least squares estimation of the slope in a linear regression and compare the exact D-optimal designs for weighted and ordinary least squares analysis.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86462424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Estimators are Hard to Compute","authors":"T. Bernholt","doi":"10.17877/DE290R-14253","DOIUrl":"https://doi.org/10.17877/DE290R-14253","url":null,"abstract":"In modern statistics, the robust estimation of parameters of a regression hyperplane is a central problem. Robustness means that the estimation is not or only slightly affected by outliers in the data. In this paper, it is shown that the following robust estimators are hard to compute: LMS, LQS, LTS, LTA, MCD, MVE, Constrained M estimator, Projection Depth (PD) and Stahel-Donoho. In addition, a data set is presented such that the ltsReg-procedure of R has probability less than 0.0001 of finding a correct answer. Furthermore, it is described, how to design new robust estimators.","PeriodicalId":10841,"journal":{"name":"CTIT technical reports series","volume":"943 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2006-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77570703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}