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The modeling of arch structures
Zbornik radova Građevinskog fakulteta Sveučilišta u Mostaru, 2008A numerical model based on exact arch finite elements with six degrees of freedom for structural analysis of arched girders is presented in this paper. This finite element is exact in the sense that it gives the exact result for a mesh of arbitrary density in the arch of constant curvature loaded in nodes.
Gotovac, Blaž +2 more
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The Spine as an Arch A New Mathematical Model
Spine, 1989A new model is presented for the static behavior of the human spine that considers it to work as an arch rather than the traditional view of a cantilever. This theory is based on limit criteria, derived from plasticity theory, which determine bounds within which the structure is mechanically stable and thereby enables the prediction of failure when ...
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ARCH modeling in the presence of missing data
2013 Asilomar Conference on Signals, Systems and Computers, 2013The problem of estimating an autoregressive conditionally heteroscedastic (ARCH) model in the presence of missing data is investigated. A two-stage least squares estimator which is easy to calculate is proposed and its strong consistency and asymptotic normality are established.
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1997
In chapter 3, we studied univariate processes \( \in = \left( {{ \in _t}} \right) \) satisfying GARCH (p, q) representations. The conditional expectations and variances were defined by $$ \left\{ {\begin{array}{*{20}{c}} {E\left( {{\varepsilon _t}/{\varepsilon _{t - 1}}} \right) = 0,} \\ {V\left( {{\varepsilon _t}/{\varepsilon _{t - 1}}} \right) = {
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In chapter 3, we studied univariate processes \( \in = \left( {{ \in _t}} \right) \) satisfying GARCH (p, q) representations. The conditional expectations and variances were defined by $$ \left\{ {\begin{array}{*{20}{c}} {E\left( {{\varepsilon _t}/{\varepsilon _{t - 1}}} \right) = 0,} \\ {V\left( {{\varepsilon _t}/{\varepsilon _{t - 1}}} \right) = {
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Pseudo‐likelihood estimation in ARCH models
Canadian Journal of Statistics, 2006AbstractThe author presents asymptotic results for the class of pseudo‐likelihood estimators in the autoregressive conditional heteroscedastic models introduced by Engle (1982). Unlike what is required for the quasi‐likelihood estimator, some estimators in the class he considers do not require the finiteness of the fourth moment of the error density ...
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Estimation and testing for ARCH models
2003Summary: This paper considers the problem of estimation and testing for ARCH models under the assumption of conditional correlation. For a bivariate model with unknown volatility parameter vector, we construct an estimator for this parameter vector using the conditional least squares estimator given by \textit{D.
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1997
The aim of this chapter is to describe the major specifications with conditional heteroscedasticity found in the literature. We first present an autoregressive model of order one with heteroscedastic errors. This simple example allows us to study in detail the existence conditions of the process and to discuss its main properties.
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The aim of this chapter is to describe the major specifications with conditional heteroscedasticity found in the literature. We first present an autoregressive model of order one with heteroscedastic errors. This simple example allows us to study in detail the existence conditions of the process and to discuss its main properties.
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ARCH MODELS: PROPERTIES, ESTIMATION AND TESTING
Journal of Economic Surveys, 1993Anil K Bera, Matthew L Higgins
exaly