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As the economic and financial characteristics of countries change, so would be their betas and correlations of their investment returns with that of the U.S. Such changes are expected to be particularly significant for emerging market nations as they strive for rapid industrialization and modernization. OLS estimator for the beta coefficient would not be the Best Linear Unbiased Estimator (BLUE) if beta is non‐stationary or changes from period to period. This paper proposes a special type of time weighted least square method (TWLS), which assigns greater weights on the regression errors in more recent periods, for estimating the current beta. This TWLS approach can tackle the problem of intertemporal heteroscedasticity and thus yields a beta that is more efficient. The breakthrough lies on the viability of the method without a‐priori knowledge or estimation of the values of the weights. This yields a significant practical advantage since the weights are unobservable in the real world. Since the Time Weighted Method estimator is the coefficient estimator of beta value for the latest period in the sample, statisticians who base their forecasts on the beta estimates derived from the Time Weighted Least Square can expect to outperform those relying on beta values obtained from conventional estimation. We use a sample of daily returns of thirty‐one emerging markets stock over the period of January 1, 2000 through December 31, 2002. We find that most of the tstatistics for the variances are significant at the 95 per cent level, indicating that the Var(s)’s are not zero for nearly every emerging‐markets. This implies that the betas for these markets do shift over time.

The purpose of this paper is to propose a new joint friction model, which can accurately model the real friction, especially in cases with sudden changes in the motion direction. The identification and sensor-less control algorithm are investigated to verify the validity of this model.

The proposed friction model is nonlinear and it considers the angular displacement and angular velocity of the joint as a secondary compensation for identification. In the present study, the authors design a pipeline – including a manually designed excitation trajectory, a weighted least squares algorithm for identifying the dynamic parameters and a hand guiding controller for the arm’s direct teaching.

Compared with the conventional joint friction model, the proposed method can effectively predict friction factors during the dynamic motion of the arm. Then friction parameters are quantitatively obtained and compared with the proposed friction model and the conventional friction model indirectly. It is found that the average root mean square error of predicted six joints in the proposed method decreases by more than 54%. The arm’s force control with the full torque using the estimated dynamic parameters is qualitatively studied. It is concluded that a light-weight industrial robot can be dragged smoothly by the hand guiding.

In the present study, a systematic pipeline is proposed for identifying and controlling an industrial arm. The whole procedure has been verified in a commercial six DOF industrial arm. Based on the conducted experiment, it is found that the proposed approach is more accurate in comparison with conventional methods. A hand-guiding demo also illustrates that the proposed approach can provide the industrial arm with the full torque compensation. This essential functionality is widely required in many industrial arms such as kinaesthetic teaching.

First, a new friction model is proposed. Based on this model, identifying the dynamic parameter is carried out to obtain a set of model parameters of an industrial arm. Finally, a smooth hand guiding control is demonstrated based on the proposed dynamic model.

The purpose of this paper is to increase the measurement accuracy of assembly deviations of an inertial navigation system, a new evaluation and optimal method of assembly metrology system is proposed, which takes into account the uncertainty from laser tracker hardware and coordinate system transformation, and is based on the Monte Carlo method.

The uncertainty model of the laser tracker is established and its parameters are obtained from the known repeated test data by kriging interpolation and the least squares method. The errors of coordinate transformation are reduced by using a weighted point matching method, and the uncertainty of the transformation parameters is obtained based on the generalized inverse theory. The weighting coefficients of each reference point are optimized by the particle swarm optimization method according to the assembly requirements.

The experiment results show that measurement error and predicted results match well, and the assembly deviation uncertainty of large component is reduced by about 10 per cent compared with the singular value decomposition method.

This paper proposes a method to evaluate and eliminate the influence of random errors of the laser tracker during evaluation process of coordinate translation parameters and assembly deviations. The proposed method would be useful to improve the assembly measurement accuracy through less measurement times.

To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.

First, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.

This method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.

The TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.

The purpose of this paper is to simulate a macrosegregation solidification benchmark by a meshless diffuse approximate method. The benchmark represents solidification of Al 4.5 wt per cent Cu alloy in a 2D rectangular cavity, cooled at vertical boundaries.

A coupled set of mass, momentum, energy and species equations for columnar solidification is considered. The phase fractions are determined from the lever solidification rule. The meshless diffuse approximate method is structured by weighted least squares method with the second-order monomials for trial functions and Gaussian weight functions. The spatial localization is made by overlapping 13-point subdomains. The time-stepping is performed in an explicit way. The pressure-velocity coupling is performed by the fractional step method. The convection stability is achieved by upstream displacement of the weight function and the evaluation point of the convective operators.

The results show a very good agreement with the classical finite volume method and the meshless local radial basis function collocation method. The simulations are performed on uniform and non-uniform node arrangements and it is shown that the effect of non-uniformity of the node distribution on the final segregation pattern is almost negligible.

The application of the meshless diffuse approximate method to simulation of macrosegregation is performed for the first time. An adaptive upwind scheme is successfully applied to the diffuse approximate method for the first time.

Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place.

A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches are used, namely, ordinary least squares using spatial dummies, a geographically weighted regression (GWR) and a spatial lag model (SLM).

The findings suggest that air quality pollutants have an adverse impact on house prices, which fluctuate across the urban area. The analysis suggests that the noise level does matter, although this varies significantly over the urban setting and varies by source.

Air quality and environmental noise pollution are important concerns for health and well-being. Noise impact seems to depend not only on the noise intensity to which dwellings are exposed but also on the nature of the noise source. This may suggest the presence of other externalities that arouse social aversion. This research presents an original study utilising advanced spatial modelling approaches. The research has value in further understanding the market impact of environmental factors and in providing findings to support local air zone management strategies, noise abatement and management strategies and is of value to the wider urban planning and public health disciplines.

The purpose of this paper is to provide the first empirical assessment of the persistence and predictability of earnings within the Georgian private sector entities.

The sample comprises of all the Georgian private sector entities who, according to the new Law of Georgia on Accounting, Reporting and Auditing (2016), had to submit their audited financial statements by 1 October 2018. Financial data has been officially withdrawn from the Ministry of Finance of Georgia and the descriptive data has been obtained by the use of Link Klipper and ScrapeStorm tools through the official “Reportal” website. The final sample consists of 450 large Georgian private sector entities. The study uses a simple, one-year-lagged earnings auto-regression to detect the persistence and predictability within the next series of earnings. A weighted least square method has been used as a statistical procedure.

The results reveal that current earnings persist within the next year’s series of earnings at less than 25%, while the reliance on current year’s earnings enables us to predict the next year’s earnings only with a chance of 20%. Further analysis has witnessed that cash flows from operations persist at less than 40% and are able of predicting the next year’s cash flows at below 35%. Overall, the properties of earnings and cash flows within the private sector of Georgia are of relatively poor quality, with the latter demonstrating higher properties compared to earnings.

The general finding on a relatively low property of earnings raises potential investors and creditors’ awareness on the valuation-usefulness of provided financial information within the private sector of Georgia. The fact that earnings are significantly less persistent and predictable compared to cash flows from operations, hints on accruals’ problematic functioning. The results presented in this paper should be of interest to a local regulator (SARAS), charged with the responsibility of successfully running a currently ongoing accounting reform of Georgia.

This is the first study that examines the persistence and predictability of earnings and cash flows from operations among the private sector entities of Georgia.

Inferences for multicomponent reliability is derived for a family of inverted exponentiated densities having common scale and different shape parameters.

Different estimates for multicomponent reliability is derived from frequentist viewpoint. Two bootstrap confidence intervals of this parametric function are also constructed.

Form a Monte-Carlo simulation study, the authors find that estimates obtained from maximum product spacing and Right-tail Anderson–Darling procedures provide better point and interval estimates of the reliability. Also the maximum likelihood estimate competes good with these estimates.

In literature several distributions are introduced and studied in lifetime analysis. Among others, exponentiated distributions have found wide applications in such studies. In this regard the authors obtain various frequentist estimates for the multicomponent reliability by considering inverted exponentiated distributions.

The elements of sales comparison for residential property depend on a package of inherent attributes that are valued by consumers. These attributes can be classified into the following categories: structural, physical, neighbourhood and environmental. A model that incorporates adjustments for floor area, age, views and amenities such as availability of recreational facilities is presented and discussed. A multiple regression analysis with transactions‐based data, using weighted least square to determine the discrete estate‐type induced price effect in the Hong Kong housing market, is also presented. The paper demonstrates how the view of negative housing attributes is capitalised into house prices. Specifically, it is shown that the residential property values are higher for estate‐type housing properties, and lower for dwelling units with a cemetery view.

The purpose of this research paper is to discuss a software reliability growth model (SRGM) based on the non‐homogeneous Poisson process which incorporates the Burr type X testing‐effort function (TEF), and to determine the optimal release‐time based on cost‐reliability criteria.

It is shown that the Burr type X TEF can be expressed as a software development/testing‐effort consumption curve. Weighted least squares estimation method is proposed to estimate the TEF parameters. The SRGM parameters are estimated by the maximum likelihood estimation method. The standard errors and confidence intervals of SRGM parameters are also obtained. Furthermore, the optimal release‐time determination based on cost‐reliability criteria has been discussed within the framework.

The performance of the proposed SRGM is demonstrated by using actual data sets from three software projects. Results are compared with other traditional SRGMs to show that the proposed model has a fairly better prediction capability and that the Burr type X TEF is suitable for incorporating into software reliability modelling. Results also reveal that the SRGM with Burr type X TEF can estimate the number of initial faults better than that of other traditional SRGMs.

The paper presents the estimation method with equal weight. Future research may include extending the present study to unequal weight.

The new SRGM may be useful in detecting more faults that are difficult to find during regular testing, and in assisting software engineers to improve their software development process.

The incorporated TEF is flexible and can be used to describe the actual expenditure patterns more faithfully during software development.