Add to ORKGIn this addendum to Verbelen et al. (2015), we present several additional examples of the calibration procedure for fitting multivariate mixtures of Erlangs to censored and truncated data.nrpages: 21status: publishe
In this addendum, we present the EM algorithm of Lee and Lin (2010) custimized for fitting mixtures ...
Modeling data on claim sizes is crucial when pricing insurance products. Such loss models require on...
Modeling data on claim sizes is crucial when pricing insurance products. Such loss models require on...
We study the estimation and use of multivariate mixtures of Erlang distributions (MME) to model depe...
We study the estimation and use of multivariate mixtures of Erlang distributions (MME) to model depe...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
We study the estimation and use of multivariate mixtures of Erlangs (MME) to model dependent multiva...
We study the estimation and use of multivariate mixtures of Erlangs (MME) to model dependent multiva...
In this addendum to Verbelen et al. (2015), we present several additional examples of the calibratio...
We study the estimation and use of multivariate mixtures of Erlangs (MME) to model dependent multiva...
We discuss how to fit mixtures of Erlangs to censored and truncated data by iteratively using the EM...
We discuss how to fit mixtures of Erlangs to censored and truncated data by iteratively using the EM...
In this addendum, we present the EM algorithm of Lee and Lin (2010) custimized for fitting mixtures ...
Modeling data on claim sizes is crucial when pricing insurance products. Such loss models require on...
Modeling data on claim sizes is crucial when pricing insurance products. Such loss models require on...
We study the estimation and use of multivariate mixtures of Erlang distributions (MME) to model depe...
We study the estimation and use of multivariate mixtures of Erlang distributions (MME) to model depe...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of...
We study the estimation and use of multivariate mixtures of Erlangs (MME) to model dependent multiva...
We study the estimation and use of multivariate mixtures of Erlangs (MME) to model dependent multiva...
In this addendum to Verbelen et al. (2015), we present several additional examples of the calibratio...
We study the estimation and use of multivariate mixtures of Erlangs (MME) to model dependent multiva...
We discuss how to fit mixtures of Erlangs to censored and truncated data by iteratively using the EM...
We discuss how to fit mixtures of Erlangs to censored and truncated data by iteratively using the EM...
In this addendum, we present the EM algorithm of Lee and Lin (2010) custimized for fitting mixtures ...
Modeling data on claim sizes is crucial when pricing insurance products. Such loss models require on...
Modeling data on claim sizes is crucial when pricing insurance products. Such loss models require on...