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Parametric statistics
About: Parametric statistics is a research topic. Over the lifetime, 39200 publications have been published within this topic receiving 765761 citations.
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TL;DR: The methodology for the simultaneous solution of ordinary differential equations and the associated first-order parametric sensitivity equations is presented, and a detailed description of its implementation as a modification of a widely disseminated implicit ODE solver is given.
Abstract: The methodology for the simultaneous solution of ordinary differential equations and the associated first-order parametric sensitivity equations is presented, and a detailed description of its implementation as a modification of a widely disseminated implicit ODE solver is given. The error control strategy ensures that local error criteria are independently satisfied by both the model and sensitivity solutions. The internal logic effectuated by this implementation is detailed. Numerical testing of the algorithm is reported; results indicate that greater reliability and improved efficiency is offered over other sensitivity analysis methods.
139 citations
TL;DR: In this article, the Tobit model is used to explain the budget share that Dutch families spend on vacations. But, the authors take account of the substantial number of zero shares, and two types of models are used.
Abstract: We analyse several limited dependent variable models explaining the budget share that Dutch families spend on vacations. To take account of the substantial number of zero shares, two types of models are used. The first is the single-equation censored regression model. We estimate and test several parametric and semi-parametric extensions of the Tobit model. Second, we consider two-equation models, in which the participation decision and the decision on the amount to spend are treated separately. The first decision is modelled as a binary choice model; the second as a conditional regression. We estimate and test parametric and semi-parametric specifications.
139 citations
TL;DR: In this article, two intrinsic criteria for runaway in fixed bed tubular reactors based on the occurrence of characteristic points in the temperature profile along the reactor were introduced, and their transposition in the partial pressure-temperature phase plane allows the derivation of some very simple formulae for the prediction of the critical values for the operating variables.
139 citations
TL;DR: The proposed method enables the design of robust sliding hyperplanes in the presence of mismatched parametric uncertainty based on quadratic stability and optimize the sliding motion by applying the guaranteed cost control idea.
139 citations
TL;DR: New results for computing and estimating the so-called Fréchet and limiting subgradients of marginal functions in real Banach spaces are derived and employed to establish new calculus rules of generalized differentiation as well as efficient conditions for Lipschitzian stability and optimality in nonlinear and nondifferentiable programming and for mathematical programs with equilibrium constraints.
Abstract: In this paper we derive new results for computing and estimating the so-called Frechet and limiting (basic and singular) subgradients of marginal functions in real Banach spaces and specify these results for important classes of problems in parametric optimization with smooth and nonsmooth data. Then we employ them to establish new calculus rules of generalized differentiation as well as efficient conditions for Lipschitzian stability and optimality in nonlinear and nondifferentiable programming and for mathematical programs with equilibrium constraints. We compare the results derived via our dual-space approach with some known estimates and optimality conditions obtained mostly via primal-space developments.
138 citations