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Control of a finite dam when the input process is either spectrally positive Levy or spectrally positive Levy reflected at its infimum
policies spectrally positive L´ evy processes spectrally pos-itive L´ evy processes reflected at its infimum scale functions exit times α-potentials total discounted and long-run-average costs.
2012/9/18
Baeet al. [6] consider the problem of optimal control of a finite dam usingPMλ,τpolicies, assuming that the input process is a compound Poisson process
with a negative drift. Lam and Lou [8] treat th...
Control of a finite dam when the input process is either spectrally positive Levy or spectrally positive Levy reflected at its infimum
policies spectrally positive L丩evy processes spectrally pos-itive L丩evy processes reflected at its infimum scale functions exit times 兛-potentials total discounted and long-run-average costs.
2012/9/18
Baeet al. [6] consider the problem of optimal control of a finite dam usingPM兩,冄policies, assuming that the input process is a compound Poisson process
with a negative drift. Lam and Lou [8] treat th...
Positive Definite $\ell_1$ Penalized Estimation of Large Covariance Matrices
Alternating direction methods Large covariance matrices Matrix norm Positive-de nite estimation Sparsity Soft-thresholding.
2012/9/18
The thresholding covariance estimator has nice asymptotic properties for estimating sparse large covariance matrices, but it often has negative eigenvalues when used in real data analysis. To simultan...
Sample size and positive false discovery rate control for multiple testing
Multiple hypothesis testing pFDR large deviations
2009/9/16
Positive false discovery rate (pFDR) is a useful overall measure of errors for multiple hypothesis testing, especially when the underlying goal is to attain one or more discoveries. Control of pFDR cr...
A rigorous lower confidence bound for the expectation of a positive random variable
rigorous lower confidence positive random variable
2009/9/16
Given an IID sample from a positive distribution, we provide a method for constructing rigorous finite sample lower confidence bounds for the expectation of the distribution. The method is based on co...