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Search: Alfred Hamerle
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1.
Unobserved heterogeneity in event history models
Title:
Unobserved heterogeneity in event history models
Author:
HansPeter Blossfeld
;
Alfred Hamerle
HansPeter Blossfeld
;
Alfred Hamerle
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Document Type:
article
URL:
http://hdl.handle.net/10.1007/BF02273551
http://hdl.handle.net/10.1007/BF02273551
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RePEc: Research Papers in Economics
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2.
Unobserved heterogeneity in hazard rate models: a test and an illustration from a study of career mobility
Title:
Unobserved heterogeneity in hazard rate models: a test and an illustration from a study of career mobility
Author:
HansPeter Blossfeld
;
Alfred Hamerle
HansPeter Blossfeld
;
Alfred Hamerle
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article
URL:
http://hdl.handle.net/10.1007/BF00151899
http://hdl.handle.net/10.1007/BF00151899
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RePEc: Research Papers in Economics
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3.
On the properties of GEE estimators in the presence of invariant covariates
Open Access
Title:
On the properties of GEE estimators in the presence of invariant covariates
Author:
Martin Spiess
;
Alfred Hamerle
Martin Spiess
;
Alfred Hamerle
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In this paper it is shown that the use of nonsingular block invariant matrices of covariates leads to `generalized estimating equations' estimators (GEE estimators; Liang, K.Y. & Zeger, S. (1986). Biometrika, 73(1), 1322) which are identical regardless of the `working' correlation matrix used. Moreover, they are efficient (McCullagh, P. (198...
In this paper it is shown that the use of nonsingular block invariant matrices of covariates leads to `generalized estimating equations' estimators (GEE estimators; Liang, K.Y. & Zeger, S. (1986). Biometrika, 73(1), 1322) which are identical regardless of the `working' correlation matrix used. Moreover, they are efficient (McCullagh, P. (1983). The Annals of Statistics, 11(1), 5967). If on the other hand only time invariant covariates are used the efficiency gain in choosing the `correct' vs. an `incorrect' correlation structure is shown to be negligible. The results of a simple simulation study suggest that although different GEE estimators are no more identical and are no more as efficient as an ML estimator, the differences are still negligible if both time and block invariant covariates are present. Key words: Generalized estimating equations; Invariant covariates; Asymptotic properties. 1 Introduction The `generalized estimating equations' approach (GEE approach) proposed.
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Year of Publication:
20090413
Source:
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper13.ps.Z
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper13.ps.Z
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Document Type:
text
Language:
en
Subjects:
Key words ; Generalized estimating equations ; Invariant covariates ; Asymptotic properties
Key words ; Generalized estimating equations ; Invariant covariates ; Asymptotic properties
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310 Collections of general statistics
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.2634
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.2634
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4.
Regression models with correlated binary response variables: A comparison of different methods in finite samples
Open Access
Title:
Regression models with correlated binary response variables: A comparison of different methods in finite samples
Author:
Martin Spiess
;
Alfred Hamerle
Martin Spiess
;
Alfred Hamerle
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The present paper deals with the comparison of the performance of different estimation methods for regression models with correlated binary responses. Throughout, we consider probit models where an underlying latent continous random variable crosses a threshold. The error variables in the unobservable latent model are assumed to be normally dist...
The present paper deals with the comparison of the performance of different estimation methods for regression models with correlated binary responses. Throughout, we consider probit models where an underlying latent continous random variable crosses a threshold. The error variables in the unobservable latent model are assumed to be normally distributed. The estimation procedures considered are (1) marginal maximum likelihood estimation using GaussHermite quadrature, (2) generalized estimation equations (GEE) techniques with an extension to estimate tetrachoric correlations in a second step, and, (3) the MECOSA approach proposed by Schepers, Arminger and Küsters (1991) using hierarchical mean and covariance structure models. We present the results of a simulation study designed to evaluate the small sample properties of the different estimators and to make some comparisons with respect to technical aspects of the estimation procedures and to bias and mean squared error of the estimators. The results show that the calculation of the ML estimator requires the most computing time, followed by the MECOSA estimator. For small and moderate sample sizes the calculation of the MECOSA estimator is problematic because of problems of convergence as well as a tendency of underestimating the variances. In large samples with moderate or high correlations of the errors in the latent model, the MECOSA estimators are not as efficient as ML or GEE estimators. The higher the `true ' value of an equicorrelation structure in the latent model and the larger the sample sizes are, the more is the efficiency gain of the ML estimator compared to the GEE and MECOSA estimators. Using the GEE approach, the ML estimates of tetrachoric correlations calculated in a second step are biased to a smaller extent than using the MECOSA approach.
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Year of Publication:
20090326
Source:
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper10.ps.Z
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper10.ps.Z
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en
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.5759
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.5759
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5.
A combined GEE/BuckleyJames method for estimating an Accelerated Failure Time Model of multivariate failure times
Open Access
Title:
A combined GEE/BuckleyJames method for estimating an Accelerated Failure Time Model of multivariate failure times
Author:
Ulrich Hornsteiner
;
Alfred Hamerle
Ulrich Hornsteiner
;
Alfred Hamerle
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The present paper deals with the estimation of a frailty model of multivariate failure times. The failure times are modeled by an Accelerated Failure Time Model including observed covariates and an unobservable frailty component. The frailty is assumed random and differs across elementary units, but is constant across the spells of a unit or a g...
The present paper deals with the estimation of a frailty model of multivariate failure times. The failure times are modeled by an Accelerated Failure Time Model including observed covariates and an unobservable frailty component. The frailty is assumed random and differs across elementary units, but is constant across the spells of a unit or a group. We develop an estimator (of the regression parameters) that combines the GEE approach (Liang and Zeger, 1986) with the BuckleyJames estimator for censored data. This estimator is robust against violations of the correlation structure and the distributional assumptions. Some simulation studies are conducted in order to study the empirical performance of the estimator. Finally, the methods are applied to data of repeated appearances of malign ventricular arrhythmias at patients with implanted defibrillator.
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Year of Publication:
20090326
Source:
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper47.ps.Z
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper47.ps.Z
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.5138
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.5138
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6.
Semiparametric EMestimation of censored linear regressionmodels for durations
Open Access
Title:
Semiparametric EMestimation of censored linear regressionmodels for durations
Author:
Alfred Hamerle
;
Michael Moller
Alfred Hamerle
;
Michael Moller
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This paper investigates the sensitivity of maximum quasi likelihood estimators of the covariate effects in duration models in the presence of misspecification due to neglected heterogeneity or misspecification of the hazard function. We consider linear models for r (T ) where T is duration and r is a known, strictly increasing function. This cla...
This paper investigates the sensitivity of maximum quasi likelihood estimators of the covariate effects in duration models in the presence of misspecification due to neglected heterogeneity or misspecification of the hazard function. We consider linear models for r (T ) where T is duration and r is a known, strictly increasing function. This class of models is also referred to as locationscale models. In the absence of censoring, Gould and Lawless (1988) have shown that maximum likelihood estimators of the regression parameters are consistent and asymptotically normally distributed under the assumption that the locationscale structure of the model is of the correct form. In the presence of censoring, however, model misspecification leads to inconsistent estimates of the regression coefficients for most of the censoring mechanisms that are widely used in practice. We propose a semiparametric EMestimator, following ideas of Ritov (1990), and Buckley and James (1979). This estimator is robust against misspecification and is highly recommended if there is heavy censoring and if there may be specification errors. We present the results of simulation experiments illustrating the performance of the proposed estimator. KEY WORDS: Censored linear regression models; accelerated failure time models; misspecified models semiparametric EMestimation; simulation study. 1 Introduction
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Year of Publication:
20090413
Source:
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper15.ps.Z
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper15.ps.Z
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.6212
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.6212
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7.
Estimation of multivariate probit models: A mixed generalized estimating/pseudoscore equations approach and some finite sample results
Open Access
Title:
Estimation of multivariate probit models: A mixed generalized estimating/pseudoscore equations approach and some finite sample results
Author:
Martin Spiess
;
Alfred Hamerle
Martin Spiess
;
Alfred Hamerle
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In the present paper a mixed approach is proposed for the simultaneously estimation of regression and correlation structure parameters in multivariate probit models using generalized estimating equations for the former and pseudoscore equations for the latter. The finite sample properties of the corresponding estimators are compared to estimato...
In the present paper a mixed approach is proposed for the simultaneously estimation of regression and correlation structure parameters in multivariate probit models using generalized estimating equations for the former and pseudoscore equations for the latter. The finite sample properties of the corresponding estimators are compared to estimators proposed by Qu, Williams, Beck and Medendorp (1992) and Qu, Piedmonte and Williams (1994) using generalized estimating equations for both sets of parameters via a Monte Carlo experiment. As a `reference' estimator for an equicorrelation model, the maximum likelihood (ML) estimator of the random effects probit model is calculated. The results show the mixed approach to be the most robust approach in the sense that the number of datasets for which the corresponding estimates converged was largest relative to the other two approaches. Furthermore, the mixed approach led to the most efficient nonML estimators and to very efficient estimators for.
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Year of Publication:
20121002
Source:
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper46.ps.Z
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper46.ps.Z
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Document Type:
text
Language:
en
Subjects:
Multivariate binary data ; Panel data ; Simulation study
Multivariate binary data ; Panel data ; Simulation study
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310 Collections of general statistics
(computed)
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URL:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.8372
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8.
Probit models: Regression parameter estimation using the ML principle despite misspecification of the correlation structure
Open Access
Title:
Probit models: Regression parameter estimation using the ML principle despite misspecification of the correlation structure
Author:
Martin Spiess, Willi Nagl
;
Alfred Hamerle
Martin Spiess, Willi Nagl
;
Alfred Hamerle
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Year of Publication:
20120402
Source:
http://epub.ub.unimuenchen.de/1461/1/paper_67.pdf
http://epub.ub.unimuenchen.de/1461/1/paper_67.pdf
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Document Type:
text
Language:
en
Subjects:
Probit models ; Regression parameter estimation
Probit models ; Regression parameter estimation
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.7598
http://epub.ub.unimuenchen.de/1461/1/paper_67.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.7598
http://epub.ub.unimuenchen.de/1461/1/paper_67.pdf
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9.
Probit models: Regression parameter estimation using the ML principle despite misspecification of the correlation structure
Open Access
Title:
Probit models: Regression parameter estimation using the ML principle despite misspecification of the correlation structure
Author:
Martin Spiess
;
Willi Nagl
;
Alfred Hamerle
Martin Spiess
;
Willi Nagl
;
Alfred Hamerle
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In this paper it is shown that using the maximum likelihood (ML) principle for the estimation of multivariate probit models leads to consistent and normally distributed pseudo maximum likelihood regression parameter estimators (PML estimators) even if the `true' correlation structure of the responses is misspecified. As a consequence, e.g. the P...
In this paper it is shown that using the maximum likelihood (ML) principle for the estimation of multivariate probit models leads to consistent and normally distributed pseudo maximum likelihood regression parameter estimators (PML estimators) even if the `true' correlation structure of the responses is misspecified. As a consequence, e.g. the PML estimator of the random effects probit model may be used to estimate the regression parameters of a model with any `true' correlation structure. This result is independent of the kind of covariates included in the model. The results of a Monte Carlo experiment show that the PML estimator of the independent binary probit model is inefficient relative to the PML estimator of the random effects binary panel probit model and two alternative estimators using the `generalized estimating equations' approach proposed by Liang and Zeger (1986), if the `true' correlations are high. If the `true' correlations are low, the differences between the estimat.
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20090412
Source:
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper67.ps.Z
ftp://ftp.stat.unimuenchen.de/pub/sfb386/paper67.ps.Z
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Document Type:
text
Language:
en
Subjects:
Categorical responses ; Maximum likelihood ; Misspecification ; Simulation
Categorical responses ; Maximum likelihood ; Misspecification ; Simulation
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.3610
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10.
Misspecified Copulas in Credit Risk Models:
Open Access
Title:
Misspecified Copulas in Credit Risk Models:
Author:
Is Gaussian
;
Alfred Hamerle
;
Daniel Rösch
;
Key Words
Is Gaussian
;
Alfred Hamerle
;
Daniel Rösch
;
Key Words
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We would like to thank an anonymous referee for providing many helpful suggestions.
We would like to thank an anonymous referee for providing many helpful suggestions.
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Year of Publication:
20090407
Source:
http://www.wiwi.uniregensburg.de/
hamerle
/mitarbeiter/assistenten/roesch/HR_JoR2005.pdf
http://www.wiwi.uniregensburg.de/
hamerle
/mitarbeiter/assistenten/roesch/HR_JoR2005.pdf
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.3600
http://www.wiwi.uniregensburg.de/hamerle/mitarbeiter/assistenten/roesch/HR_JoR2005.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.3600
http://www.wiwi.uniregensburg.de/hamerle/mitarbeiter/assistenten/roesch/HR_JoR2005.pdf
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(105) Hamerle, Alfred
(32) Rösch, Daniel
(18) Liebig, Thilo
(15) Knapp, Michael
(14) Alfred Hamerle
(12) The Pennsylvania State University CiteSeerX...
(10) Plank, Kilian
(9) Scheule, Harald
(8) Wildenauer, Nicole
(7) Blossfeld, HansPeter
(7) Jobst, Rainer
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(5) Schropp, HansJochen
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(4) Martin Spiess
(4) Spiess, M.
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(2) Editorial Board
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(2) Hornsteiner, U.
(2) Igl, Andreas
(2) Karlheinz Tödter
(2) Lerner, Matthias
(2) Nagl, Willi
(2) Singer, Hermann
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(2) Wadè, Markus
(1) Brachinger, Hans Wolfgang
(1) Dartsch, Andreas
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(1) Spieß, Martin
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Author:
Subject
(83) 330 wirtschaft
(34) 310 statistik
(8) ddc 510
(8) sonderforschungsbereich 386
(5) credit risk
(4) bank regulation
(4) ddc 330
(4) g21
(4) kreditrisiko
(3) asset correlation
(3) basel ii
(3) c1
(3) default correlation
(3) portfolio management
(3) probability of default
(3) schätzung
(2) 330 economics
(2) credit ratings
(2) default probability
(2) deutschland
(2) kreditwürdigkeit
(2) prognoseverfahren
(2) welt
(1) arbitrage cdos
(1) arbitragegeschäft
(1) asymptotic properties
(1) bond representation
(1) c13
(1) c23
(1) c41
(1) categorical responses
(1) cdo pricing
(1) collateralized debt obligations cdo
(1) credit rating
(1) eigenkapitalvorschriften
(1) estimation risk
(1) expected loss profile
(1) finanzderivat
(1) finanzmarktkrise
(1) g01
(1) g12
(1) g24
(1) generalized estimating equations
(1) invariant covariates
(1) key words
(1) kreditsicherung
(1) logit model
(1) makroökonomischer einfluss
(1) maximum likelihood
(1) misspecification
(1) multivariate binary data
(1) panel data
(1) pd
(1) point in time
(1) probit model
(1) probit models
(1) regression parameter estimation
(1) risk management jel codes
(1) simulation
(1) simulation study
(1) statistischer fehler
(1) systematic risk of cdo tranches
(1) theorie
(1) value at risk
(1) wahrscheinlichkeitsrechnung
(1) wertpapieranalyse
Subject:
Dewey Decimal Classification (DDC)
(14) Statistics [31*]
(7) Economics [33*]
(1) Literature, rhetoric & criticism [80*]
Dewey Decimal Classification (DDC):
Year of Publication
(11) 2009
(9) 2004
(8) 2005
(8) 2008
(7) 1996
(6) 2006
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