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published in Advances in Stochastic Models for Reliability, Quality and Safety
"... The capability index Cpk for a process, that produces parts with normally distributed characteristic X, is defined as Cpk =min(U − µ, µ − L)/(3σ)=(T −µ − ν)/(3σ), where U and L are upper and lower specification limits for X, µ and σ are process mean and standard deviation, and ν =(U + L)/2, T =(U ..."
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The capability index Cpk for a process, that produces parts with normally distributed characteristic X, is defined as Cpk =min(U − µ, µ − L)/(3σ)=(T −µ − ν)/(3σ), where U and L are upper and lower specification limits for X, µ and σ are process mean and standard deviation, and ν =(U + L)/2, T =(U − L)/2. UsingasampleX1,...,Xn of independent observations from N (µ, σ 2)Chouetal. (1990) (with clarification by Kushler and Hurley (1992)) showed how to get lower confidence bounds for Cpk.Here we extend this methodology to cover the situation where samples come in batches and the intra batch correlation reduces the amount of independent information.In parallel we also apply this extension to the closely related tolerance bounds or confidence bounds for quantiles.Introducing the simple trick of effective sample size these problems are linked quite successfully to existing tables for tolerance bounds or Cpk confidence bounds.The basic idea is to “approximate ” the complicated data situation with an i.i.d. scenario with reduced overall sample size.The approximation is anchored by analysis to the two extreme situations where the within batch correlation is zero or one.For the inbetween
Quality Control Techniques and Issues in GPS Applications: Stochastic Modeling and Reliability Test
"... This paper summarizes a new quality control method including a new cycleslip correction method which enables instantaneous correction (i.e., using only current epoch’s GPS carrierphase measurements) at the data quality control stage and a new approach for the stochastic model for kinematic GPS pos ..."
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This paper summarizes a new quality control method including a new cycleslip correction method which enables instantaneous correction (i.e., using only current epoch’s GPS carrierphase measurements) at the data quality control stage and a new approach for the stochastic model for kinematic GPS
Contour Tracking By Stochastic Propagation of Conditional Density
, 1996
"... . In Proc. European Conf. Computer Vision, 1996, pp. 343356, Cambridge, UK The problem of tracking curves in dense visual clutter is a challenging one. Trackers based on Kalman filters are of limited use; because they are based on Gaussian densities which are unimodal, they cannot represent s ..."
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Cited by 658 (24 self)
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simultaneous alternative hypotheses. Extensions to the Kalman filter to handle multiple data associations work satisfactorily in the simple case of point targets, but do not extend naturally to continuous curves. A new, stochastic algorithm is proposed here, the Condensation algorithm  Conditional
Bayesian Analysis of Stochastic Volatility Models
, 1994
"... this article is to develop new methods for inference and prediction in a simple class of stochastic volatility models in which logarithm of conditional volatility follows an autoregressive (AR) times series model. Unlike the autoregressive conditional heteroscedasticity (ARCH) and gener alized ARCH ..."
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Cited by 588 (25 self)
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this article is to develop new methods for inference and prediction in a simple class of stochastic volatility models in which logarithm of conditional volatility follows an autoregressive (AR) times series model. Unlike the autoregressive conditional heteroscedasticity (ARCH) and gener alized
Learning Stochastic Logic Programs
, 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a firstorder r ..."
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Cited by 1181 (79 self)
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Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first
Stochastic volatility: likelihood inference and comparison with ARCH models
 Review of Economic Studies
, 1998
"... In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihoodbased framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating offse ..."
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Cited by 582 (41 self)
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In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihoodbased framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating
Stochastic Perturbation Theory
, 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
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Cited by 886 (35 self)
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. In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variation in the perturbed quantity. Up to the higherorder terms that are ignored in the expansion, these statistics tend to be more realistic than perturbation bounds obtained in terms of norms. The technique is applied to a number of problems in matrix perturbation theory, including least squares and the eigenvalue problem. Key words. perturbation theory, random matrix, linear system, least squares, eigenvalue, eigenvector, invariant subspace, singular value AMS(MOS) subject classifications. 15A06, 15A12, 15A18, 15A52, 15A60 1. Introduction. Let A be a matrix and let F be a matrix valued function of A. Two principal problems of matrix perturbation theory are the following. Given a matrix E, pr...
Jumps and stochastic volatility: Exchange rate processes implicit in Deutsche Mark options
, 1993
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Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora
, 1997
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The Valuation of Options for Alternative Stochastic Processes
 Journal of Financial Economics
, 1976
"... This paper examines the structure of option valuation problems and develops a new technique for their solution. It also introduces several jump and diffusion processes which have nol been used in previous models. The technique is applied lo these processes to find explicit option valuation formulas, ..."
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Cited by 661 (4 self)
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This paper examines the structure of option valuation problems and develops a new technique for their solution. It also introduces several jump and diffusion processes which have nol been used in previous models. The technique is applied lo these processes to find explicit option valuation formulas
Results 1  10
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1,821,159