Krivobokova, Tatyana

[["dc.bibliographiccitation.firstpage","199"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","The Journal of Economic Inequality"],["dc.bibliographiccitation.lastpage","225"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Klasen, Stephan"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Greb, Friederike"],["dc.contributor.author","Lahoti, Rahul"],["dc.contributor.author","Pasaribu, Syamsul Hidayat"],["dc.contributor.author","Wiesenfarth, Manuel"],["dc.date.accessioned","2017-11-28T09:52:29Z"],["dc.date.available","2017-11-28T09:52:29Z"],["dc.date.issued","2016"],["dc.description.abstract","We critically review conceptual and empirical issues surrounding the derivation of the international poverty line, expressed in PPP-adjusted dollars and linked to various rounds of the International Comparison Program (ICP). We find that there are some limitations in the current estimation of these lines, but show that statistically superior methods lead to lines that are relatively robust and confirm the .25 using 2005 PPPs and suggest .67–1.71 using 2011 PPPs (or close to the .90 proposed by the World Bank if we follow the World Bank’s approach of adjusting inflation rates in some countries); they also roughly confirm the current shape of the proposed ‘weakly relative’ poverty line. Using the new absolute line based on 2011 PPPs would lead to substantially lower poverty in our estimation. The extent of the decline depends on whether and how one treats China, India, and Indonesia differently from other countries in the 2005 and 2011 PPPs. More seriously, we note that the dependence on successive ICP rounds creates conceptual and empirical problems that have become worse over time so that we suggest that it would be best to consider alternatives to the current reliance on ICP rounds and the resulting PPPs. As a short-term solution we propose to fix the international poverty line in national currencies using either the 2005 or 2011 level; in the medium term, we argue for global poverty measurement based on internationally coordinated national poverty measurement."],["dc.identifier.doi","10.1007/s10888-016-9324-8"],["dc.identifier.fs","614716"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10567"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eissn","1573-8701"],["dc.relation.issn","1569-1721"],["dc.subject","Poverty; World Bank; Dollar-a-day; Weakly relative poverty"],["dc.title","International income poverty measurement: which way now?"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","529"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Biometrika"],["dc.bibliographiccitation.lastpage","544"],["dc.bibliographiccitation.volume","96"],["dc.contributor.author","Claeskens, Gerda"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Opsomer, J. D."],["dc.date.accessioned","2017-09-07T11:50:09Z"],["dc.date.available","2017-09-07T11:50:09Z"],["dc.date.issued","2009"],["dc.description.abstract","We study the class of penalized spline estimators, which enjoy similarities to both regression splines, without penalty and with fewer knots than data points, and smoothing splines, with knots equal to the data points and a penalty controlling the roughness of the fit. Depending on the number of knots, sample size and penalty, we show that the theoretical properties of penalized regression spline estimators are either similar to those of regression splines or to those of smoothing splines, with a clear breakpoint distinguishing the cases. We prove that using fewer knots results in better asymptotic rates than when using a large number of knots. We obtain expressions for bias and variance and asymptotic rates for the number of knots and penalty parameter."],["dc.identifier.doi","10.1093/biomet/asp035"],["dc.identifier.gro","3145858"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/3588"],["dc.notes.intern","mathe"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.publisher","Oxford University Press (OUP)"],["dc.relation.issn","0006-3444"],["dc.subject","Mean squared error Nonparametric regression Penalty Regression spline Smoothing spline Introduction Penalized spline"],["dc.title","Asymptotic properties of penalized spline estimators"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","852"],["dc.bibliographiccitation.issue","490"],["dc.bibliographiccitation.journal","Journal of the American Statistical Association"],["dc.bibliographiccitation.lastpage","863"],["dc.bibliographiccitation.volume","105"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Kneib, Thomas"],["dc.contributor.author","Claeskens, Gerda"],["dc.date.accessioned","2017-09-07T11:50:08Z"],["dc.date.available","2017-09-07T11:50:08Z"],["dc.date.issued","2010"],["dc.description.abstract","In this article we construct simultaneous confidence bands for a smooth curve using penalized spline estimators. We consider three types of estimation methods: (a) as a standard (fixed effect) nonparametric model, (b) using the mixed-model framework with the spline coefficients as random effects, and (c) a full Bayesian approach. The volume-of-tube formula is applied for the first two methods and compared with Bayesian simultaneous confidence bands from a frequentist perspective. We show that the mixed-model formulation of penalized splines can help obtain, at least approximately, confidence bands with either Bayesian or frequentist properties. Simulations and data analysis support the proposed methods. The R package ConfBands accompanies the article."],["dc.identifier.doi","10.1198/jasa.2010.tm09165"],["dc.identifier.gro","3145857"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/3587"],["dc.notes.intern","mathe"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.publisher","Informa UK Limited"],["dc.relation.issn","0162-1459"],["dc.subject","B-spline Bayesian penalized spline Confidence band Mixed model Penalization"],["dc.title","Simultaneous Confidence Bands for Penalized Spline Estimators"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","127"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Information and Software Technology"],["dc.bibliographiccitation.lastpage","147"],["dc.bibliographiccitation.volume","46"],["dc.contributor.author","Pfahl, Dietmar"],["dc.contributor.author","Laitenberger, Oliver"],["dc.contributor.author","Ruhe, Günther"],["dc.contributor.author","Dorsch, Jörg"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.date.accessioned","2017-09-07T11:50:05Z"],["dc.date.available","2017-09-07T11:50:05Z"],["dc.date.issued","2004"],["dc.description.abstract","The increasing demand for software project managers in industry requires strategies for the development of management-related knowledge and skills of the current and future software workforce. Although several educational approaches help to develop the necessary skills in a university setting, few empirical studies are currently available to characterise and compare their effects. This paper presents the results of a twice replicated experiment that evaluates the learning effectiveness of using a process simulation model for educating computer science students in software project management. While the experimental group applied a System Dynamics simulation model, the control group used the well-known COCOMO model as a predictive tool for project planning. The results of each empirical study indicate that students using the simulation model gain a better understanding about typical behaviour patterns of software development projects. The combination of the results from the initial experiment and the two replications with metaanalysis techniques corroborates this finding. Additional analysis shows that the observed effect can mainly be attributed to the use of the simulation model in combination with a web-based role-play scenario. This finding is strongly supported by information gathered from the debriefing questionnaires of subjects in the experimental group. They consistently rated the simulation-based role-play scenario as a very useful approach for learning about issues in software project management."],["dc.identifier.doi","10.1016/s0950-5849(03)00115-0"],["dc.identifier.gro","3145863"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/3594"],["dc.language.iso","en"],["dc.notes.intern","mathe"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0950-5849"],["dc.subject","COCOMO Learning effectiveness Replicated experiment Software project management education System dynamics simulation"],["dc.title","Evaluating the learning effectiveness of using simulations in software project management education: results from a twice replicated experiment"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","171"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Bayesian Analysis"],["dc.bibliographiccitation.lastpage","196"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Greb, Friederike"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Munk, Axel"],["dc.contributor.author","Cramon-Taubadel, Stephan von"],["dc.date.accessioned","2017-09-07T11:46:55Z"],["dc.date.available","2017-09-07T11:46:55Z"],["dc.date.issued","2014"],["dc.description.abstract","In this article we discuss estimation of generalized threshold regression models in settings when the threshold parameter lacks identifiability. In particular, if estimation of the regression coefficients is associated with high uncertainty and/or the difference between regimes is small, estimators of the threshold and, hence, of the whole model can be strongly affected. A new regularized Bayesian estimator for generalized threshold regression models is proposed. We derive conditions for superiority of the new estimator over the standard likelihood one in terms of mean squared error. Simulations confirm excellent finite sample properties of the suggested estimator, especially in the critical settings. The practical relevance of our approach is illustrated by two real-data examples already analyzed in the literature."],["dc.identifier.doi","10.1214/13-BA850"],["dc.identifier.gro","3142214"],["dc.identifier.isi","000332837600012"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5799"],["dc.language.iso","en"],["dc.notes.intern","WoS Import 2017-03-10"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.eissn","1936-0975"],["dc.relation.issn","1931-6690"],["dc.title","Regularized Bayesian Estimation of Generalized Threshold Regression Models"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","256"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Test"],["dc.bibliographiccitation.lastpage","259"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Munk, Axel"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.date.accessioned","2018-11-07T08:27:36Z"],["dc.date.available","2018-11-07T08:27:36Z"],["dc.date.issued","2009"],["dc.identifier.doi","10.1007/s11749-009-0152-z"],["dc.identifier.isi","000267165800005"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/16240"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1133-0686"],["dc.title","Comments on: Goodness-of-fit tests in mixed models"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.subtype","letter_note"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Computational and Graphical Statistics"],["dc.bibliographiccitation.lastpage","20"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Crainiceanu, Ciprian M."],["dc.contributor.author","Kauermann, Göran"],["dc.date.accessioned","2017-09-07T11:50:04Z"],["dc.date.available","2017-09-07T11:50:04Z"],["dc.date.issued","2008"],["dc.description.abstract","This article proposes a numerically simple method for locally adaptive smoothing. The heterogeneous regression function is modeled as a penalized spline with a varying smoothing parameter modeled as another penalized spline. This is formulated as a hierarchical mixed model, with spline coefficients following zero mean normal distribution with a smooth variance structure. The major contribution of this article is to use the Laplace approximation of the marginal likelihood for estimation. This method is numerically simple and fast. The idea is extended to spatial and non-normal response smoothing."],["dc.identifier.doi","10.1198/106186008x287328"],["dc.identifier.gro","3145860"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/3591"],["dc.notes.intern","mathe"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.publisher","Informa UK Limited"],["dc.relation.issn","1061-8600"],["dc.subject","Function of locally varying complexity Hierarchical mixed model Laplace approximation"],["dc.title","Fast Adaptive Penalized Splines"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","219"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Bayesian Analysis"],["dc.bibliographiccitation.lastpage","238"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Serra, Paulo"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.date.accessioned","2020-12-10T18:41:47Z"],["dc.date.available","2020-12-10T18:41:47Z"],["dc.date.issued","2017"],["dc.description.abstract","In this paper we develop and study adaptive empirical Bayesian smoothing splines. These are smoothing splines with both smoothing parameter and penalty order determined via the empirical Bayes method from the marginal likelihood of the model. The selected order and smoothing parameter are used to construct adaptive credible sets with good frequentist coverage for the underlying regression function. We use these credible sets as a proxy to show the superior performance of adaptive empirical Bayesian smoothing splines compared to frequentist smoothing splines."],["dc.identifier.arxiv","1411.6860"],["dc.identifier.doi","10.1214/16-BA997"],["dc.identifier.gro","3145848"],["dc.identifier.isi","000398972500009"],["dc.identifier.issn","1936-0975"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77674"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Int Soc Bayesian Analysis"],["dc.relation.issn","1936-0975"],["dc.relation.issn","1931-6690"],["dc.title","Adaptive Empirical Bayesian Smoothing Splines"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","971"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Journal of Applied Statistics"],["dc.bibliographiccitation.lastpage","987"],["dc.bibliographiccitation.volume","45"],["dc.contributor.author","Yoon, Jisu"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.date.accessioned","2020-12-10T18:14:49Z"],["dc.date.available","2020-12-10T18:14:49Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1080/02664763.2017.1346065"],["dc.identifier.eissn","1360-0532"],["dc.identifier.issn","0266-4763"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74628"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Treatments of non-metric variables in partial least squares and principal component analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","900"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","American Journal of Agricultural Economics"],["dc.bibliographiccitation.lastpage","916"],["dc.bibliographiccitation.volume","95"],["dc.contributor.author","Greb, Friederike"],["dc.contributor.author","Cramon-Taubadel, Stephan von"],["dc.contributor.author","Krivobokova, Tatyana"],["dc.contributor.author","Munk, Axel"],["dc.date.accessioned","2017-09-07T11:47:39Z"],["dc.date.available","2017-09-07T11:47:39Z"],["dc.date.issued","2013"],["dc.description.abstract","The threshold vector error correction model is a popular tool for the analysis of spatial price transmission. In the literature, the profile likelihood estimator is the preferred choice for estimating this model. Yet, in many settings this estimator performs poorly. In particular, if the true thresholds are such that one or more regimes contain only a small number of observations, if unknown model parameters are numerous, or if parameters differ little between regimes, the profile likelihood estimator displays large bias and variance. Such settings are likely when studying price transmission. We analyze the weaknesses of the profile likelihood approach and propose an alternative regularized Bayesian estimator, which was developed for simpler but related threshold models. Simulation results show that the regularized Bayesian estimator outperforms profile likelihood in the estimation of threshold vector error correction models. Two empirical applications demonstrate the relevance of this new estimator for spatial price transmission analysis."],["dc.identifier.doi","10.1093/ajae/aat006"],["dc.identifier.gro","3142332"],["dc.identifier.isi","000322022300006"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/7108"],["dc.language.iso","en"],["dc.notes.intern","WoS Import 2017-03-10"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.issn","0002-9092"],["dc.title","The Estimation of Threshold Models in Price Transmission Analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]