1,721,181 research outputs found
The Rao regression-type estimator in ranked set sampling
No full textWe revisit the Rao regression-type estimator in the context of the ranked set sampling. The expression of the minimum mean squared error is obtained and a simulation study is carried out to evaluate the gain of efficiency of the considered estimator upon some competitive estimators
Distributed-Lag Structural Equation Modelling: an Application to Impact Assessment of Research Activity on European Agriculture
No full textStructural equation modelling is a class of statistical models typically employed to analyse the dependence relationships among a set of variables. We define an extension of the class where variables are related by distributed-lag linea regression models, in order to account for temporal delays in the dependence relationships among the variables. Our proposal is applied to impact assessment of research activity on European Agriculture
Relabelling in Bayesian mixture models by pivotal units
Full text linkA simple procedure based on relabelling to deal with label switching when exploring complex posterior distributions by MCMC algorithms is proposed. Although it cannot be generalized to any situation, it may be handy in many applications because of its simplicity and low computational burden. A possible area where it proves to be useful is when deriving a sample for the posterior distribution arising from finite mixture models when no simple or rational ordering between the components is available
Exploring Non Linear Structures in Range-Based Volatility Time Series
No full textIn this paper we focus on the use of Extreme Learning Machines (ELMs) to appropriately capture the nonlinear dynamics of the range based estimators. The results on all the assets in the S&P500 index show that ELMs produce residuals without neglected nonlinearitie
THE INFLUENCE OF CORRELATION AND LOADING ON M-V EFFICIENT RETENTIONS IN VARIABLE QUOTA SHARE PROPORTIONAL REINSURANCE.
No full textBased on our recent discovery of closed form formulae of efficient Mean
Variance retentions in variable quota-share proportional reinsurance under group
correlation, we analyzed the influence on the efficient frontier of two key variables,
correlation and safety loading levels, in a single period stylized problem.We found
a clear separated influence of each variable (given the level of the other) and a surprising
joint influence of both on the efficient se
Conditional Quantile Estimation for Linear ARCH Models with MIDAS Components
No full textRecent financial crises have put an increased emphasis on methods devoted to risk management. Among a plethora of risk measures proposed in literature, the Value-at-Risk (VaR) plays still today a prominent role. Despite some criticisms, the VaR measures are fundamental in order to adequately set aside risk capital. For this reason, during the last decades the literature has been interested in proposing as much as possible accurate VaR models. Recently, the quantile regression approach has been used to directly forecast the VaR measures. We embed the linear AutoRegressive Conditional Heteroscedasticity (ARCH) model with MIDAS (MI(xed)-DA(ta) Sampling) term in such a quantile regression (QR) framework. The proposed model, named Quantile ARCH-MIDAS (Q–ARCH–MIDAS), allows to benefit from the information coming from variables observed at different frequencies with respect to that of the variable of interest. Moreover, the QR context brings additional advantages, such as the robustness to the presence of outliers and the lack of distributional assumptions
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