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Bounds for the Sum of Dependent Risks and Worst Value-at-Risk with Monotone Marginal Densities
Complete mixability Monotone density Sum of dependent risks Value-at- Risk
2016/1/25
In quantitative risk management, it is important and challenging to find sharp bounds for the distribution of the sum of dependent risks with given marginal distributions, but an unspecified dependenc...
Bounds for the Sum of Dependent Risks and Worst Value-at-Risk with Monotone Marginal Densities
Complete mixability Monotone density Sum of dependent risks Value-at- Risk
2016/1/20
In quantitative risk management, it is important and challenging to find sharp bounds for the distribution of the sum of dependent risks with given marginal distributions, but an unspecified dependenc...
Tractable Fitting with Convex Polynomials via Sum-of-Squares
Tractable Fitting Convex Polynomials Sum-of-Squares
2015/7/10
We consider the problem of fitting given data (u_1,y_1),...,(u_m,y_m), where u_i in {bf R}^n and y_i in {bf R}, with a convex polynomial f$. A technique to solve this problem using sum of squares pol...
Segmentation of ARX-Models Using Sum-of-Norms Regularization
Segmentation Regularization ARX-models
2015/7/9
Segmentation of time-varying systems and signals into models whose parameters are piecewise constant in time is an important and well studied problem. It is here formulated as a least-squares problem ...
Smoothed state estimates under abrupt changes using sum-of-norms regularization
Smoothing Sparsity Regularization Change detection
2015/7/9
The presence of abrupt changes, such as impulsive and load disturbances, commonly occur in applications, but make the state estimation problem considerably more difficult than in the standard setting ...
The problem of maximizing a sum of sigmoidal functions over a convex constraint set arises in many application areas. This objective captures the idea of decreasing marginal returns to investment, and...
Test MaxEnt in Social Strategy Transitions with Experimental Two-Person Constant Sum 2$\times$2 Games
maximum entropy principle social strategy transitions constant sum game experimental eco-nomics
2012/9/18
Using laboratory experimental data, we test the uncertainty of social state transitions in various competing environments of fixed paired two-person constantsum 2×2 games. It firstly shows that,the di...
The AEP algorithm for the fast computation of the distribution of the sum of dependent random variables
convolution istribution functions
2011/7/5
We propose a new algorithm to compute numerically the distribution function of the sum of $d$ dependent, non-negative random variables with given joint distribution.
On a general zero-sum stochastic game with optimal stopping
a general zero-sum stochastic game optimal stopping
2009/9/24
In the paper a general zeroaum stochastic game with
stopping is considered. Using the so-called penalty method the author
shows the existence of the value of the game under fairly general
assumptio...
Addendum to the paper "On a general zero-sum stochastic game with optimal stopping"
Addendum a general zero-sum stochastic game optimal stopping
2009/9/24
Addendum to the paper "On a general zero-sum stochastic game with optimal stopping"。
On zero - sum stochastic games with general state space. I
zero - sum stochastic games general state space
2009/9/24
On zero - sum stochastic games with general state space. I。
On zero-sum stochastic games with general state space. II
zero-sum stochastic games general state space
2009/9/24
On zero-sum stochastic games with general state space. II。
On a general zero-sum stochastic game with stopping strategy for one player and continuous strategy for the other
a general zero-sum stochastic game stopping strategy
2009/9/24
On a general zero-sum stochastic game with stopping strategy for one player and continuous strategy for the other。
Acknowledgment of Priority: When Does a Randomly Weighted Self-normalized Sum Converge in Distribution? (Elect. Comm. in Probab. 10 (2005), 70--81)
Domain of attraction selfCnormalize sums regular variation
2009/4/27
Christian Houdre has kindly pointed us to a paper by A. Fuks, A. Joffe and J. Teugels, where their Theorem 5.3 is our Proposition 3 in the case 0
When Does a Randomly Weighted Self-normalized Sum Converge in Distribution?
Domain of attraction selfCnormalize sums regular variation
2009/4/24
We determine exactly when a certain randomly weighted, self--normalized sum converges in distribution, partially verifying a 1965 conjecture of Leo Breiman. We, then, apply our results to characterize...