3,815 research outputs found
On approximation of Markov binomial distributions
For a Markov chain with the state space
, the random variable is said to follow a Markov
binomial distribution. The exact distribution of , denoted ,
is very computationally intensive for large (see Gabriel [Biometrika 46
(1959) 454--460] and Bhat and Lal [Adv. in Appl. Probab. 20 (1988) 677--680])
and this paper concerns suitable approximate distributions for
when is stationary. We conclude that the negative binomial and
binomial distributions are appropriate approximations for when
is greater than and less than ,
respectively. Also, due to the unique structure of the distribution, we are
able to derive explicit error estimates for these approximations.Comment: Published in at http://dx.doi.org/10.3150/09-BEJ194 the Bernoulli
(http://isi.cbs.nl/bernoulli/) by the International Statistical
Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm
On the effects of changing mortality patterns on investment, labour and consumption under uncertainty
In this paper we extend the consumption-investment life cycle model for an
uncertain-lived agent, proposed by Richard (1974), to allow for
exible labor supply. We further study the consumption, labor supply and portfolio decisions of an agent facing age-dependent mortality risk, as presented by UK actuarial life tables spanning the time period from 1951-2060 (including mortality forecasts). We find that historical changes in mortality produces significant changes in portfolio investment (more risk taking), labour (decrease of hours) and consumption level (shift to higher level) contributing
up to 5% to GDP growth during the period from 1980 until 2010
Switching and Rectification of a Single Light-sensitive Diarylethene Molecule Sandwiched between Graphene Nanoribbons
The 'open' and 'closed' isomers of the diarylethene molecule that can be
converted between each other upon photo-excitation are found to have
drastically different current-voltage characteristics when sandwiched between
two graphene nanoribbons (GNRs). More importantly, when one GNR is metallic and
another one is semiconducting, strong rectification behavior of the 'closed'
diarylethene isomer with the rectification ratio >10^3 is observed. The
surprisingly high rectification ratio originates from the band gap of GNR and
the bias-dependent variation of the lowest unoccupied molecular orbital (LUMO)
of the diarylethene molecule, the combination of which completely shuts off the
current at positive biases. Results presented in this paper may form the basis
for a new class of molecular electronic devices.Comment: The Journal of Chemical Physics 135 (2011
Electrical transport across metal/two-dimensional carbon junctions: Edge versus side contacts
Metal/two-dimensional carbon junctions are characterized by using a nanoprobe
in an ultrahigh vacuum environment. Significant differences were found in bias
voltage (V) dependence of differential conductance (dI/dV) between edge- and
side-contact; the former exhibits a clear linear relationship (i.e., dI/dV
\propto V), whereas the latter is characterized by a nonlinear dependence,
dI/dV \propto V3/2. Theoretical calculations confirm the experimental results,
which are due to the robust two-dimensional nature of the carbon materials
under study. Our work demonstrates the importance of contact geometry in
graphene-based electronic devices
Optimal management and inflation protection for defined contribution pension plans
Due to the increasing risk of inflation and diminishing pension benefits, insurance companies have started selling in°ation-linked products. Selling such products the insurance company takes over some or all of the inflation risk from their customers. On the other side financial derivatives which are linked to inflation such as inflation linked bonds are traded on financial markets and appear to be of increasing popularity. The insurance company can use these products to hedge its own inflation risk. In this article we study how to optimally manage a pension fund taking positions in a money market account, a stock and an inflation linked bond, while financing investments through a continuous stochastic income stream such as the plan member's contributions. We use the martingale method in order to compute an analytic expression for the optimal strategy and express it in terms of observable market variables.Pension mathematics; in°ation; long-term investment; stochastic optimal control; martingale method
A New Adaptive LSSVR with Online Multikernel RBF Tuning to Evaluate Analog Circuit Performance
Focusing on the analog circuit performance evaluation demand of fast time responding online, a novel evaluation strategy based on adaptive Least Squares Support Vector Regression (LSSVR) which employs multikernel RBF is proposed in this paper. The superiority of the multi-kernel RBF has more flexibility to the kernel function online such as the bandwidths tuning. And then the decision parameters of the kernel parameters determine the input signal to map to the feature space deduced that a well plant model by discarding redundant features. Experiment adopted the typical circuit Sallen-Key low pass filter to prove the proposed evaluation strategy via the eight performance indexes. Simulation results reveal that the testing speed together with the evaluation performance, especially the testing speed of the proposed, is superior to that of the traditional LSSVR and ε-SVR, which is suitable for promotion online
The Effects of the Internet and Mobile Services on Urban Household Expenditures
In recent years, the economy of China has entered a new normal state and the economic growth rate has decelerated. The telecommunications industry as a national strategic and basic industry, is also facing up with some dilemma. Information consumption is a comprehensive concept including e-commerce, communications, broadband services, online games and so on. On this basis, this paper employs the almost ideal demand system(AIDS) to explore the impact that information consumption has made to residential consumption expenditure and the change of the consumption structure. Ac-cording to empirical analysis, finally we can draw the following conclusions: The income elasticity of information consumption is greater than 1, which means the income demand is flexible. And the self-price elasticity of information consumption is negative and the absolute value is between 0 and 1. It means that the price of information consumption is not flexible
Robust Fault Tolerant Control for Discrete-Time Dynamic Systems With Applications to Aero Engineering Systems
Unexpected faults in actuators and sensors may degrade the reliability and safety of aero engineering systems. Therefore, there is motivation to develop integrated fault tolerant control techniques with applications to aero engineering systems. In this paper, discrete-time dynamic systems, in the presence of simultaneous actuator/sensor faults, partially decoupled unknown input disturbances, and sensor noises, are investigated. A jointly state/fault estimator is formulated by integrating an unknown input observer, augmented system approach, and optimization algorithm. Unknown input disturbances can be either decoupled by an unknown input observer, or attenuated by a linear matrix inequality optimization, enabling the estimation error to be input-to-state stable. Estimator-based signal compensation is then implemented to mitigate adverse effects from the unanticipated actuator and sensor faults. A pre-designed controller, which maintains normal system behaviors under a fault-free scenario, is allowed to work along with the presented fault tolerant mechanism of the signal compensations. The fault-tolerant closed-loop system can be ensured to mitigate the effects from the faults, guarantee the input-to-state stability, and satisfy the required robustness performance. The proposed fault estimation and fault tolerant control methods are developed for both discrete-time linear and discrete-time Lipschitz nonlinear systems. Finally, the proposed techniques are applied to a jet engine system and a flight control system for simulation validation
Reweighted lp Constraint LMS-Based Adaptive Sparse Channel Estimation for Cooperative Communication System
This paper studies the issue of sparsity adaptive channel reconstruction in time-varying cooperative
communication networks through the amplify-and-forward transmission scheme. A new sparsity adaptive system
identification method is proposed, namely reweighted norm ( < < ) penalized least mean square(LMS)algorithm.
The main idea of the algorithm is to add a norm penalty of sparsity into the cost function of the LMS algorithm. By doing
so, the weight factor becomes a balance parameter of the associated norm adaptive sparse system identification.
Subsequently, the steady state of the coefficient misalignment vector is derived theoretically, with a performance upper
bounds provided which serve as a sufficient condition for the LMS channel estimation of the precise reweighted norm.
With the upper bounds, we prove that the ( < < ) norm sparsity inducing cost function is superior to the
reweighted norm. An optimal selection of for the norm problem is studied to recover various sparse channel
vectors. Several experiments verify that the simulation results agree well with the theoretical analysis, and thus
demonstrate that the proposed algorithm has a better convergence speed and better steady state behavior than other LMS
algorithms
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