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Weighted sums and residual . . .
, 2012
"... In the context of a timevarying ARprocess we study both function indexed weighted sums, and sequential residual empirical processes. As for the latter it turns out that somewhat surprisingly, under appropriate assumptions, the nonparametric estimation of the parameter functions has a negligible a ..."
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In the context of a timevarying ARprocess we study both function indexed weighted sums, and sequential residual empirical processes. As for the latter it turns out that somewhat surprisingly, under appropriate assumptions, the nonparametric estimation of the parameter functions has a negligible
ESTIMATING WEIGHTED SUMS IN WINNOW
"... Chawla et al. introduced a way to use the Markov chain Monte Carlo method to estimate weighted sums in multiplicative weight update algorithms when the number of inputs is exponential. But their algorithm still required extensive simulation of the Markov chain in order to get accurate estimates of t ..."
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Chawla et al. introduced a way to use the Markov chain Monte Carlo method to estimate weighted sums in multiplicative weight update algorithms when the number of inputs is exponential. But their algorithm still required extensive simulation of the Markov chain in order to get accurate estimates
On Convergence of Weighted Sums of LNQD Random
"... We discuss the strong convergence for weighted sums of linearly negative quadrant dependent(LNQD) random variables under suitable conditions and the central limit theorem for weighted sums of an LNQD case is also considered. In addition, we derive some corollaries in LNQD setting. ..."
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We discuss the strong convergence for weighted sums of linearly negative quadrant dependent(LNQD) random variables under suitable conditions and the central limit theorem for weighted sums of an LNQD case is also considered. In addition, we derive some corollaries in LNQD setting.
Server Selection by using Weighted Sum and Revised Weighted Sum Decision Models
"... The role of the information technology is growing rapidly in the world of business, to communicate with the customers effectively. Computer network is the back bone of any organization. It helps in effective utilization of resources such as time, money etc. Server plays an important role in the netw ..."
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. by using the weighted sum model and revised weighted sum decision models. On the basis of calculated actual worth, the ranking has been done by using weighted sum model and, revised weighted sum decision model after normalization, resulting IBM at the top, following HP and SMS servers.
Some stochastic inequalities for weighted sums
, 910
"... We compare weighted sums of i.i.d. positive random variables according to the usual stochastic order. The main inequalities are derived using majorization techniques under certain logconcavity assumptions. Specifically, let Yi be i.i.d. random variables on R+. Assuming that log Yi has a logconcave ..."
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We compare weighted sums of i.i.d. positive random variables according to the usual stochastic order. The main inequalities are derived using majorization techniques under certain logconcavity assumptions. Specifically, let Yi be i.i.d. random variables on R+. Assuming that log Yi has a log
On the Complete Convergence of Weighted Sums for Dependent Random Variables
"... Abstract. We study the limiting behavior of weighted sums for negatively associated (NA) random variables. We extend results in ..."
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Abstract. We study the limiting behavior of weighted sums for negatively associated (NA) random variables. We extend results in
STRONG STABILITY OF WEIGHTED SUMS OF NA RANDOM VARIABLES
, 2004
"... We study the almost sure (strong) stability of weighted sums of NA random variables and ..."
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We study the almost sure (strong) stability of weighted sums of NA random variables and
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