Contemporaneous outlier blocks (additive or reallocation) caused by special events frequently occur in repeated business time series. When the time series have strong inter-series dependence, shrinkage estimation techniques provide improved estimates of the time series model parameters and of the outlier block. A bootstrap estimate of the covariance matrix of the vector of outlier magnitudes en...

This work aims the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic...

Background: Radiotherapy with large mantle field is an effective technique in increasing the risk of secondary cancers among HL (Hodgkin Lymphoma) patients; therefore, it is essential to choose an effective treatment field including the least medical conditions in radiotherapy.Objective: The present study aimed to plan separate fields for neck and mediastinum using various energies, to compare ...

We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also incorporates direct and modulating effects of input vari...

Wind power point forecasting is the primary method to deal with its uncertainty. However, in many applications, the probabilistic interval of wind power is more useful than traditional point forecasting. Methods to determine the probabilistic interval of wind power point forecasting value is very essential to power system operations. Based on the bootstrap method, this paper proposed a wavelet ...

There is a growing literature on unit root testing in threshold autoregressive models. This paper makes two contributions to the literature. First, an asymptotic theory is developed for unit root testing in a threshold autoregression, in which the errors are allowed to be dependent and heterogeneous, and the lagged level of the dependent variable is employed as the threshold variable. The asymp...

In this paper, the pricing performances of two learning networks, namely an artificial neural network and a bootstrap aggregating ensemble network, were compared when Johannesburg Stock Exchange (JSE) Top 40 European call options in modern option framework using constructed implied volatility surface. addition to this, numerical accuracy better performing was Monte Carlo simulation separate exp...