Parameter Estimation in Minification Processes

In this article it is proved that the stationary Markov sequences generated by minification models are ergodic and uniformly mixing. These results are used to establish the optimal properties of estimators for the parameters in the model. The problem of estimating the parameters in the exponential minification model is discussed in detail.

Strength and serviceability performance of beams reinforced with GFRP bars in flexure

Glass fiber reinforced polymer (GFRP) rebars have been identified as an alternate construction material for reinforcing concrete during the last decade primarily due to its strength and durability related characteristics. These materials have strength higher than steel, but exhibit linear stress–strain response up to failure. Furthermore, the modulus of elasticity of GFRP is significantly lower than that of steel. This reduced stiffness often controls the design of the GFRP reinforced concrete elements. In the present investigation, GFRP reinforced beams designed based on limit state principles have been examined to understand their strength and serviceability performance. A block type rotation failure was observed for GFRP reinforced beams, while flexural failure was observed in geometrically similar control beams reinforced with steel rebars. An analytical model has been proposed for strength assessment accounting for the failure pattern observed for GFRP reinforced beams. The serviceability criteria for design of GFRP reinforced beams appear to be governed by maximum crack width. An empirical model has been proposed for predicting the maximum width of the cracks. Deflection of these GFRP rebar reinforced beams has been predicted using an earlier model available in the literature. The results predicted by the analytical model compare well with the experimental data

Product autoregressive models for non-negative variables

When variables in time series context are non-negative, such as for volatility, survival time or wave heights, a multiplicative autoregressive model of the type Xt = Xα t−1Vt , 0 ≤ α < 1, t = 1, 2, . . . may give the preferred dependent structure. In this paper, we study the properties of such models and propose methods for parameter estimation. Explicit solutions of the model are obtained in the case of gamma marginal distribution