Pages that link to "Item:Q2866005"
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The following pages link to Modeling dependent risks with multivariate Erlang mixtures (Q2866005):
Displaying 38 items.
- On mixed Erlang reinsurance risk: aggregation, capital allocation and default risk (Q303732) (← links)
- Bivariate lower and upper orthant value-at-risk (Q487568) (← links)
- On two families of bivariate distributions with exponential marginals: aggregation and capital allocation (Q495473) (← links)
- Modeling dependence based on mixture copulas and its application in risk management (Q603180) (← links)
- Fitting the Erlang mixture model to data via a GEM-CMM algorithm (Q1643834) (← links)
- CMPH: a multivariate phase-type aggregate loss distribution (Q1648668) (← links)
- A class of mixture of experts models for general insurance: theoretical developments (Q2010898) (← links)
- Estimation of multivariate generalized gamma convolutions through Laguerre expansions (Q2074286) (← links)
- Conditional multivariate distributions of phase-type for a finite mixture of Markov jump processes given observations of sample path (Q2146463) (← links)
- Multivariate matrix-exponential affine mixtures and their applications in risk theory (Q2172057) (← links)
- Fitting multivariate Erlang mixtures to data: a roughness penalty approach (Q2222165) (← links)
- Bayesian credibility under a bivariate prior on the frequency and the severity of claims (Q2234765) (← links)
- On some multivariate Sarmanov mixed Erlang reinsurance risks: aggregation and capital allocation (Q2397867) (← links)
- Multivariate mixtures of Erlangs for density estimation under censoring (Q2398460) (← links)
- Collective risk models with dependence (Q2421408) (← links)
- On the analysis of a general class of dependent risk processes (Q2444713) (← links)
- On multivariate discounted compound renewal sums with time-dependent claims in the presence of reporting/payment delays (Q2520463) (← links)
- Can a regulatory risk measure induce profit-maximizing risk capital allocations? The case of conditional tail expectation (Q2665868) (← links)
- A bivariate Laguerre expansions approach for joint ruin probabilities in a two-dimensional insurance risk process (Q2670126) (← links)
- Dependence modelling in insurance via copulas with skewed generalised hyperbolic marginals (Q2699605) (← links)
- A Reconciliation of the Top-Down and Bottom-Up Approaches to Risk Capital Allocations: Proportional Allocations Revisited (Q3385437) (← links)
- ON SOME PROPERTIES OF A CLASS OF MULTIVARIATE ERLANG MIXTURES WITH INSURANCE APPLICATIONS (Q4563733) (← links)
- ON SARMANOV MIXED ERLANG RISKS IN INSURANCE APPLICATIONS (Q4563734) (← links)
- FITTING MIXTURES OF ERLANGS TO CENSORED AND TRUNCATED DATA USING THE EM ALGORITHM (Q4563757) (← links)
- EFFICIENT ESTIMATION OF ERLANG MIXTURES USING iSCAD PENALTY WITH INSURANCE APPLICATION (Q4563784) (← links)
- Signs of dependence and heavy tails in non-life insurance data (Q4575381) (← links)
- Risk model based on the first-order integer-valued moving average process with compound Poisson distributed innovations (Q4583611) (← links)
- Delta Boosting Machine with Application to General Insurance (Q4689973) (← links)
- AGGREGATION OF DEPENDENT RISKS IN MIXTURES OF EXPONENTIAL DISTRIBUTIONS AND EXTENSIONS (Q4691248) (← links)
- A CLASS OF MIXTURE OF EXPERTS MODELS FOR GENERAL INSURANCE: APPLICATION TO CORRELATED CLAIM FREQUENCIES (Q4972120) (← links)
- Authors’ Reply: On the Class of Erlang Mixtures with Risk Theoretic Applications - Discussion by David C. M. Dickson; Howard R. Waters (Q5019732) (← links)
- “On the Class of Erlang Mixtures with Risk Theoretic Applications,” Gordon E. Willmot and Jae-Kyung Woo, April 2007 (Q5019774) (← links)
- On the analysis of a discrete-time risk model with INAR(1) processes (Q5083403) (← links)
- Aggregating Risks with Partial Dependence Information (Q5379244) (← links)
- Minimum capital requirement and portfolio allocation for non-life insurance: a semiparametric model with conditional value-at-risk (CVaR) constraint (Q6088771) (← links)
- On a Dirichlet process mixture representation of phase-type distributions (Q6121778) (← links)
- Micro-level prediction of outstanding claim counts based on novel mixture models and neural networks (Q6173881) (← links)
- Loss modeling with the size-biased lognormal mixture and the entropy regularized EM algorithm (Q6573825) (← links)
