We introduce arbitrary precision arithmetic to resolve practical difficulties arising in the identification analysis of dynamic stochastic general equilibrium (DSGE) models. A three-step procedure is proposed address local and global empirical distance between The method applied monetary fiscal policy interaction models, revealing exact observational equivalence a small-scale model an indetermi...

The intuitionistic linguistic set (ILS) is an extension of linguisitc variable. To overcome the drawback of using single real number to represent membership degree and non-membership degree for ILS, the concept of interval-valued intuitionistic linguistic set (IVILS) is introduced through representing the membership degree and non-membership degree with intervals for ILS in this paper. The oper...

It is shown that a probabilistic Turing acceptor or transducer running within space bound S can be simulated by a time S 2 parallel machine and therefore by a space S 2 deterministic machine. (Previous simulations ran in space $6.) In order to achieve these simulations, known algorithms are extended for the computation of determinants in small arithmetic parallel time to computations having sma...

This paper is devoted to the construction of Boltzmann samplers according to various distributions, and uses stochastic bias on the parameter of a Boltzmann sampler, to produce a sampler with a different distribution for the size of the output. As a significant application, we produce Boltzmann samplers for words defined by regular specifications containing shuffle operators and linear recursio...

Probabilistic arithmetic involves the calculation of the distribution of arithmetic functions of random variables. This work on probabilistic arithmetic began as an investigation into the possibility o f adapting existing numerical procedures (developal for fixed numbers) to handle random variables (by replacing the basic operations of arithmetic by the appropriate convolutions). The general id...

Generally, vagueness is modelled by a fuzzy approach and randomness by a stochastic approach. But in some cases, a decision maker may prefer using interval numbers as coefficients of an inexact relationship. In this paper, we define a linear programming problem involving interval numbers as an extension of the classical linear programming problem to an inexact environment. By using a new simple...

Starting from on a recently introduced Gaussian class bivariate Weibull stochastic model, the probability density and the cumulative distribution functions of the product (Z1 Z2) c and the ratio (Z1/Z2) c, when Z1 and Z2 are correlated Weibull random variables belonging to this class (c > 0), are derived in closed form. Moreover, using the inequality between arithmetic and geometric mean, a uni...

This paper presents four diierent approaches for estimating the average value of a soil property over a region, say a province, from point data: 1) arithmetic average, 2) declustered mean, 3) block kriging, and 4) stochastic simulation. The last two techniques are based on geostatistics which allows one to account for the pattern of spatial dependence of observations while providing a measure o...

Low bitwidth integer arithmetic has been widely adopted in hardware implementations of deep neural network inference applications. However, despite the promised energy-efficiency improvements demanding edge applications, use low for training remains limited. Unlike inference, demands high dynamic range and numerical accuracy quality results, making low-bitwidth particularly challenging. To addr...