نتایج جستجو برای: partially negative data
تعداد نتایج: 2918678 فیلتر نتایج به سال:
in this paper, linear data envelopment analysis models are used to estimate markowitz efficient frontier. conventional dea models assume non-negative values for inputs and outputs. however, variance is the only variable in these models that takes non-negative values. therefore, negative data models which the risk of the assets had been used as an input and expected return was the output are uti...
A partially linear model is often estimated in a two-stage procedure, which involves estimating the nonlinear component conditional on initially estimated linear coefficients. We propose a sampling procedure that aims to simultaneously estimate the linear coefficients and bandwidths involved in the Nadaraya-Watson estimator of the nonlinear component. The performance of this sampling procedure ...
This study aims to determine the magnitude of influence variables FDR, NPF, Firm Size, Infalsi, and GDP on ROA at Rural Bank Syaria in Indonesia. The population used is registered with OJK. data secondary derived from financial reports issued by OJK for 2016-2020 period. research method quantitative pane regression analysis supported Eviews 9 as a processing application. sample this was 99 BPRS...
It is known that determinining whether a DEC-POMDP, namely, a cooperative partially observable stochastic game (POSG), has a cooperative strategy with positive expected reward is complete for NEXP. It was not known until now how cooperation affected that complexity. We show that, for competitive POSGs, the complexity of determining whether one team has a positive-expected-reward strategy is com...
DECISION-THEORETIC META-REASONING IN PARTIALLY OBSERVABLE AND DECENTRALIZED SETTINGS
A recent insight in the field of decentralized partially observable Markov decision processes (Dec-POMDPs) is that it is possible to convert a Dec-POMDP to a non-observable MDP, which is a special case of POMDP. This technical report provides an overview of this reduction and pointers to related literature.
Decision theoretic planning in ai bymeans of solving Partially ObservableMarkov decision processes (pomdps) has been shown to be both powerful and versatile. However, such approaches are computationally hard and, from a design stance, are not necessarily intuitive for conceptualising many problems. We propose a novel method for solving pomdps, which provides a designer with a more intuitive mea...
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