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1.
Generalized
Open Access
Title:
Generalized
Author:
Vinzenz Erhardt
;
A Timedependent
;
Vinzenz Erhardt
;
Gee For
;
Vinzenz Erhardt
;
A Timedependent
;
Vinzenz Erhardt
Vinzenz Erhardt
;
A Timedependent
;
Vinzenz Erhardt
;
Gee For
;
Vinzenz Erhardt
;
A Timedependent
;
Vinzenz Erhardt
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Description:
Simulation study Application to patent outsourcing rates Summary and outlook
Simulation study Application to patent outsourcing rates Summary and outlook
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20150301
Source:
http://www.biostat.uzh.ch/research/workshop/
Erhardt
_Vinzenz_Zurich07.pdf
http://www.biostat.uzh.ch/research/workshop/
Erhardt
_Vinzenz_Zurich07.pdf
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Document Type:
text
Language:
en
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Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.563.542
http://www.biostat.uzh.ch/research/workshop/Erhardt_Vinzenz_Zurich07.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.563.542
http://www.biostat.uzh.ch/research/workshop/Erhardt_Vinzenz_Zurich07.pdf
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2.
Locating Multiple Interacting Quantitative Trait Loci with the ZeroInflated Generalized Poisson Regression
Title:
Locating Multiple Interacting Quantitative Trait Loci with the ZeroInflated Generalized Poisson Regression
Author:
Vinzenz Erhardt
;
Malgorzata Bogdan
;
Claudia Czado
Vinzenz Erhardt
;
Malgorzata Bogdan
;
Claudia Czado
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Description:
We consider the problem of locating multiple interacting quantitative trait loci (QTL) influencing traits measured in counts. In many applications the distribution of the count variable has a spike at zero. Zeroinflated generalized Poisson regression (ZIGPR) allows for an additional probability mass at zero and hence an improvement in the detec...
We consider the problem of locating multiple interacting quantitative trait loci (QTL) influencing traits measured in counts. In many applications the distribution of the count variable has a spike at zero. Zeroinflated generalized Poisson regression (ZIGPR) allows for an additional probability mass at zero and hence an improvement in the detection of significant loci. Classical model selection criteria often overestimate the QTL number. Therefore, modified versions of the Bayesian Information Criterion (mBIC and EBIC) were successfully used for QTL mapping. We apply these criteria based on ZIGPR as well as simpler models. An extensive simulation study shows their good power detecting QTL while controlling the false discovery rate. We illustrate how the inability of the Poisson distribution to account for overdispersion leads to an overestimation of the QTL number and hence strongly discourages its application for identifying factors influencing count data. The proposed method is used to analyze the mice gallstone data of Lyons et al. (2003). Our results suggest the existence of a novel QTL on chromosome 4 interacting with another QTL previously identified on chromosome 5. We provide the corresponding code in R. ; Computational Biology/Bioinformatics, Statistical Models, quantitative trait loci, count data, model selection criteria, zero inflated Poisson regression
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Document Type:
article
URL:
http://www.bepress.com/cgi/viewcontent.cgi?article=1545&context=sagmb
http://www.bepress.com/cgi/viewcontent.cgi?article=1545&context=sagmb
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3.
A Method for approximately sampling highdimensional Count Variables with prespecified Pearson Correlation
Open Access
Title:
A Method for approximately sampling highdimensional Count Variables with prespecified Pearson Correlation
Author:
Vinzenz Erhardt
;
Claudia Czado
Vinzenz Erhardt
;
Claudia Czado
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Description:
We suggest an approximative method for sampling highdimensional count random variables with a specified Pearson correlation. As in the continuous case copulas can be used to construct multivariate discrete distributions. We utilize Gaussian copulas for the construction. A major task is to determine the appropriate copula parameters to obtain th...
We suggest an approximative method for sampling highdimensional count random variables with a specified Pearson correlation. As in the continuous case copulas can be used to construct multivariate discrete distributions. We utilize Gaussian copulas for the construction. A major task is to determine the appropriate copula parameters to obtain the specified target correlation. Very often, the fact that for the Gaussian copula the correlation matrix of the multivariate normal distribution is not equal to the correlation of the sampled (discrete) outcomes, is simply neglected. We will introduce an optimization routine to determine the copula parameters sequentially using bisection. Thereby, we need to break our Tdimensional copula down to a decomposition of bivariate copulas with only one parameter each. We use Cvines, a graphical tool to organize such paircopula decompositions of highdimensional distributions. We will illustrate that our sampling approach generates accurate results even in high dimensions in several settings with Poisson, generalized Poisson, zeroinflated generalized Poisson and Negative Binomial margins for a variety of marginal parameters and outperforms a widely used ’naive ’ sampling approach. An implementation of our algorithm for R is available as package corcounts on ’The Comprehensive R Archive Network ’ (CRAN). Keywords: algorithm; longitudinal; pair copula construction; Cvine; partial correlation. 1
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Year of Publication:
20091119
Source:
http://wwwm4.ma.tum.de/Papers/
Erhardt
/
erhardt
sampling.pdf
http://wwwm4.ma.tum.de/Papers/
Erhardt
/
erhardt
sampling.pdf
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Document Type:
text
Language:
en
DDC:
310 Collections of general statistics
(computed)
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.1847
http://wwwm4.ma.tum.de/Papers/Erhardt/erhardtsampling.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.1847
http://wwwm4.ma.tum.de/Papers/Erhardt/erhardtsampling.pdf
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4.
Sampling Count Variables with specified Pearson Correlation  a Comparison between a naive and a Cvine Sampling Approach
Open Access
Title:
Sampling Count Variables with specified Pearson Correlation  a Comparison between a naive and a Cvine Sampling Approach
Author:
Vinzenz Erhardt
;
Claudia Czado
Vinzenz Erhardt
;
Claudia Czado
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Description:
Erhardt
and Czado (2008) suggest an approximative method for sampling highdimensional count random variables with a specified Pearson correlation. They utilize Gaussian copulae for the construction of multivariate discrete distributions. A major task is to determine the appropriate copula parameters for the achievement of a specified target corr...
Erhardt
and Czado (2008) suggest an approximative method for sampling highdimensional count random variables with a specified Pearson correlation. They utilize Gaussian copulae for the construction of multivariate discrete distributions. A major task is to determine the appropriate copula parameters for the achievement of a specified target correlation.
Erhardt
and Czado (2008) develop an optimization routine to determine these copula parameters sequentially. Thereby, they use paircopula decompositions of ndimensional distributions, i.e. a decomposition consisting only of bivariate copula with one parameter each. Cvines, a graphical tool to organize such paircopula decompositions, are used to select a possible decomposition. In the paper mentioned, the approach was compared to the NORTA method for discrete margins described in Avramidis, Channouf, and L’Ecuyer (2008). Here we will compare it to a widely used naive sampling approach for an even larger variety of marginal distributions such as the Poisson, generalized Poisson, Negative Binomial and zeroinflated Generalized Poisson distribution.
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20111025
Source:
http://wwwm4.ma.tum.de/Papers/
Erhardt
/cvinevsnaivewebpage.pdf
http://wwwm4.ma.tum.de/Papers/
Erhardt
/cvinevsnaivewebpage.pdf
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Document Type:
text
Language:
en
DDC:
310 Collections of general statistics
(computed)
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.1234
http://wwwm4.ma.tum.de/Papers/Erhardt/cvinevsnaivewebpage.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.1234
http://wwwm4.ma.tum.de/Papers/Erhardt/cvinevsnaivewebpage.pdf
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5.
including zeroclaims
Open Access
Title:
including zeroclaims
Author:
Vinzenz Erhardt
;
Claudia Czado
Vinzenz Erhardt
;
Claudia Czado
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Description:
Modelling dependent yearly claim totals
Modelling dependent yearly claim totals
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20120319
Source:
http://wwwm4.ma.tum.de/Papers/
Erhardt
/pccmarginals
erhardt
czado.pdf
http://wwwm4.ma.tum.de/Papers/
Erhardt
/pccmarginals
erhardt
czado.pdf
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Document Type:
text
Language:
en
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Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.215.5555
http://wwwm4.ma.tum.de/Papers/Erhardt/pccmarginalserhardtczado.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.215.5555
http://wwwm4.ma.tum.de/Papers/Erhardt/pccmarginalserhardtczado.pdf
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6.
A method for approximately sampling highdimensional countvariableswithprespecifiedPearsoncorrelation.Submitted for publication.Preprint available at...
Open Access
Title:
A method for approximately sampling highdimensional countvariableswithprespecifiedPearsoncorrelation.Submitted for publication.Preprint available at http://wwwm4.ma.tum.de/Papers/index.html
Author:
Vinzenz Erhardt
;
Claudia Czado
Vinzenz Erhardt
;
Claudia Czado
Minimize authors
Description:
We suggest an approximative method for sampling highdimensional random variables with a specified Pearson correlation matrix. We sample from dependent vectors using paircopula constructions (PCC) and use Cvines, a graphical tool to organize such PCC. Thereby, we choose bivariate Gaussian copulas for the construction. A major task is to determ...
We suggest an approximative method for sampling highdimensional random variables with a specified Pearson correlation matrix. We sample from dependent vectors using paircopula constructions (PCC) and use Cvines, a graphical tool to organize such PCC. Thereby, we choose bivariate Gaussian copulas for the construction. A major task is to determine the appropriate copula parameterstoobtainthespecifiedtargetcorrelation.Wewillintroduceasequentialandveryfastrootfinding routine to approximate them using bisection. We will illustrate that our sampling approach generates accurate results even in high dimensions and for relatively small sample sizes in several settings with Poisson, generalized Poisson, zeroinflated generalized Poisson and Negative Binomial margins in a variety of settings. We show its advantages over the NORTA method for discrete margins. An implementation of our algorithm for R is available as package corcounts on CRAN. Keywords: algorithm; longitudinal count data; pair copula construction; Cvine; input modeling.
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20120420
Source:
http://wwwm4.ma.tum.de/Papers/
Erhardt
/
erhardt
sampling.pdf
http://wwwm4.ma.tum.de/Papers/
Erhardt
/
erhardt
sampling.pdf
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Document Type:
text
Language:
en
DDC:
310 Collections of general statistics
(computed)
Rights:
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.84
http://wwwm4.ma.tum.de/Papers/Erhardt/erhardtsampling.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.84
http://wwwm4.ma.tum.de/Papers/Erhardt/erhardtsampling.pdf
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7.
Modelling dependent yearly claim totals including zeroclaims in . . .
Open Access
Title:
Modelling dependent yearly claim totals including zeroclaims in . . .
Author:
Vinzenz Erhardt
;
Claudia Czado
Vinzenz Erhardt
;
Claudia Czado
Minimize authors
Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20111025
Source:
http://wwwm4.ma.tum.de/Papers/
Erhardt
/pccmarginals
erhardt
czado.pdf
http://wwwm4.ma.tum.de/Papers/
Erhardt
/pccmarginals
erhardt
czado.pdf
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Document Type:
text
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en
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Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.2713
http://wwwm4.ma.tum.de/Papers/Erhardt/pccmarginalserhardtczado.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.2713
http://wwwm4.ma.tum.de/Papers/Erhardt/pccmarginalserhardtczado.pdf
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8.
Locating multiple interacting quantitative trait loci with the zero . . .
Open Access
Title:
Locating multiple interacting quantitative trait loci with the zero . . .
Author:
Vinzenz Erhardt
;
Małgorzata Bogdan
;
Claudia Czado
Vinzenz Erhardt
;
Małgorzata Bogdan
;
Claudia Czado
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Year of Publication:
20100322
Source:
http://wwwm4.ma.tum.de/Papers/
Erhardt
/
erhardt
bogdanczado.pdf
http://wwwm4.ma.tum.de/Papers/
Erhardt
/
erhardt
bogdanczado.pdf
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en
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Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.484
http://wwwm4.ma.tum.de/Papers/Erhardt/erhardtbogdanczado.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.484
http://wwwm4.ma.tum.de/Papers/Erhardt/erhardtbogdanczado.pdf
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9.
outsourcing
Open Access
Title:
outsourcing
Author:
Claudia Czado
;
Vinzenz Erhardt
;
Aleksey Min
;
Stefan Wagner
Claudia Czado
;
Vinzenz Erhardt
;
Aleksey Min
;
Stefan Wagner
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Description:
Zeroinflated generalized Poisson models with regression effects on the mean, dispersion and zeroinflation level applied to patent
Zeroinflated generalized Poisson models with regression effects on the mean, dispersion and zeroinflation level applied to patent
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The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20080701
Source:
http://wwwm4.ma.tum.de/Papers/Czado/Czado
Erhardt
MinWagner.ps
http://wwwm4.ma.tum.de/Papers/Czado/Czado
Erhardt
MinWagner.ps
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Document Type:
text
Language:
en
Subjects:
maximum likelihood estimator ; overdispersion ; patent outsourcing ; Vuong test ; zeroinflated generalized Poisson regression ; zeroinflation 1 Corresponding author
maximum likelihood estimator ; overdispersion ; patent outsourcing ; Vuong test ; zeroinflated generalized Poisson regression ; zeroinflation 1 Corresponding author
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.7018
http://wwwm4.ma.tum.de/Papers/Czado/CzadoErhardtMinWagner.ps
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.7018
http://wwwm4.ma.tum.de/Papers/Czado/CzadoErhardtMinWagner.ps
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10.
Corresponding author.
Open Access
Title:
Corresponding author.
Author:
Claudia Czado
;
Vinzenz Erhardt
;
Aleksey Min
Claudia Czado
;
Vinzenz Erhardt
;
Aleksey Min
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Description:
Zeroinflated generalized Poisson models with regression effects on the mean, dispersion and zeroinflation level applied to patent
Zeroinflated generalized Poisson models with regression effects on the mean, dispersion and zeroinflation level applied to patent
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Contributors:
The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20130808
Source:
http://www.statistik.lmu.de/sfb386/papers/dsp/paper482.pdf
http://www.statistik.lmu.de/sfb386/papers/dsp/paper482.pdf
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Document Type:
text
Language:
en
Subjects:
maximum likelihood estimator ; overdispersion ; patent outsourcing ; Vuong test ; zeroinflated generalized Poisson regression ; zeroinflation 1
maximum likelihood estimator ; overdispersion ; patent outsourcing ; Vuong test ; zeroinflated generalized Poisson regression ; zeroinflation 1
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.319.7878
http://www.statistik.lmu.de/sfb386/papers/dsp/paper482.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.319.7878
http://www.statistik.lmu.de/sfb386/papers/dsp/paper482.pdf
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(17) Vinzenz Erhardt
(16) The Pennsylvania State University CiteSeerX...
(15) Claudia Czado
(4) Aleksey Min
(3) Erhardt, Vinzenz
(3) Stefan Wagner
(3) Technische Universität München
(2) Czado, Claudia
(2) Lehrstuhl Für Mathematische Statistik
(2) Małgorzata Bogdan
(2) Min, Aleksey
(1) A Timedependent
(1) Czado, Claudia (Prof., Ph.D.)
(1) Fahrmeir, Ludwig (Prof. Dr.)
(1) Frigessi, Arnoldo (Prof.)
(1) Gee For
(1) Lazyload Yes
(1) Malgorzata Bogdan
(1) Needscompilation No
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(6) overdispersion
(5) maximum likelihood estimator
(5) patent outsourcing
(5) vuong test
(5) zero inflated generalized poisson regression
(2) ddc 510
(2) generalized poisson regression
(2) longitudinal count data
(2) zero inflation 1
(2) zero inflation 1 corresponding author
(1) ddc 310
(1) generalized estimating equations
(1) i e for individual parameters for each cluster
(1) in order to allow for regression
(1) run rcounts reg
(1) sonderforschungsbereich 386
(1) zero inflation
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