Evaluation of industry tendencies in Uzbekistan

2020 ◽  
Vol 8 ◽  
Author(s):  
Radjabov Bunyod Abduhalilovich
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Industrial Production ◽  
Industrial Development ◽  
Least Squares Method ◽  
Development Trends ◽  
Industry Development

The article proposes a method for assessing trends in industrial development in Uzbekistan. The least-squares method of the regression model was used to estimate industry development trends. Development trends are assessed based on the index of change in the final and theoretical values of industrial production.

scholarly journals The Impact of Public Debt on the Economic Growth of Jordan: An Empirical Study (2000- 2015)

2017 ◽  
Vol 6 (2) ◽  
pp. 114 ◽  
Author(s):  
Tawfiq Ahmad Mousa ◽  
Abudallah. M. LShawareh
Keyword(s):  
Economic Growth ◽  
Empirical Study ◽  
Regression Model ◽  
Least Squares ◽  
Public Debt ◽  
Least Squares Method ◽  
Negative Impact ◽  
External Debt ◽  
Using Data ◽  
The Impact

In the last two decades, Jordan’s economy has been relied on public debt in order to enhance the economic growth. As such, an understanding  of the dynamics between public debt and economic growth is very important in addressing the obstacles to economic growth. The study investigates the impact of public debt on economic growth using data from 2000 to 2015. The study employs least squares method and regression model to capture the impact of public debt on economic growth. The results of the analysis indicate that there is a negative impact of total public debt, especially the external debt on economic growth. 

scholarly journals Current state and prospects of innovative industry development of Ukraine

2020 ◽  
pp. 38-43
Author(s):  
Mohammed Younus Hasan Alghadhywi
Keyword(s):  
Industrial Production ◽  
Industrial Development ◽  
Environmentally Friendly ◽  
Inclusive Development ◽  
High Tech ◽  
Innovative Development ◽  
Processing Industry ◽  
Industry Development ◽  
The World ◽  
Innovation Processes

Purpose. The purpose of the study is to analyse the development trends of Ukrainian industry and identify ways to solve existing problems based on the intensification of innovation processes. Methodology of research. During the research methods generally accepted in economic science were applied, in particular: statistical and graphic – for definition of Ukrainian industry development tendencies; comparative analysis – to compare the Ukrainian industry and the world; system generalization – in substantiating the directions of industry innovative development intensification. Findings. The current trends in the development of industrial production in Ukraine, which are characterized by falling production volumes and negative changes in the structure of the industry, are revealed. The reduction of industrial production is revealed, which occurs mainly due to the curtailment of the processing industry enterprises activity. Negative changes in the structure of the industry are revealed, among which the increase in the share of low-tech productions with a significant decrease in medium-tech and moderate –high-tech ones are highlighted. Based on the correlation between industrial production indicators and GDP dynamics, it is proved that industry forms the foundation of the country`s social and economic development. It was found that the Ukrainian economy lags far behind the development of the world`s leading countries in terms of its material, resource, and energy intensity. The article proves that the issue of industrial development based on the intensification of innovation processes in Ukraine needs radical changes in reforming the management mechanisms of innovation processes and relations between science, society, business, and government to intensify investment activities support the technological development of industry, the introduction of environmentally friendly production. Originality. The analysis of the state of Ukraine`s industry and substantiation of the need for its innovative development was further developed, in the context of which measures were proposed to intensify innovation processes, which, in addition to existing ones, provide for the formation of a managing mechanism for innovative industrial development; coordination of industrial sector development policy with the goals of sustainable and inclusive development; introduction of environmentally friendly industrial production; expansion of cross-border economic and environmental cooperation; development of the strategy of development of the industry of Ukraine taking into account the European experience. Practical value. The results of the study are the basis for solving practical problems of improving the situation and the transition to innovative industrial development in Ukraine. Key words: industry of Ukraine, processing industry, structure of industrial production, industry innovative development.

Fuzzy Regression Model Based on Geometric Centroid and Incentre Points and Application to Performance Evaluation

2020 ◽  
Vol 28 (02) ◽  
pp. 269-288
Author(s):  
Yanbing Gong ◽  
Lin Xiang ◽  
Gaofeng Liu
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Estimation Error ◽  
Triangular Fuzzy Number ◽  
Fuzzy Regression ◽  
Distance Method ◽  
Fuzzy Input ◽  
Fuzzy Regression Model ◽  
Fuzzy Linear Regression Model

Fuzzy regression model is developed to construct the relationship between independent variable and dependent variable in a fuzzy environment. In order to increase the explanatory performance of fuzzy regression model, the least-squares method usually is applied to determine the numeric coefficients based on the concept of distance. In this paper, we consider the fuzzy linear regression model with fuzzy input, fuzzy output and crisp parameters and introduce a new distance based on the geometric centroid and incentre points (GCIP) of triangular fuzzy number, merge least-squares method with the new GCIP distance and propose least-squares GCIP distance method. Finally, an example of employee job performance is given to illustrate the effectiveness and feasibility of the method. Comparisons with existing methods show that total estimation error using the same distance criterion, the explanatory performance of the GCIP method is satisfactory, and the calculation is relatively simple.

Characteristics of Corrosion Degradation in Carbon Steel Pipelines

2012 ◽  
Vol 626 ◽  
pp. 807-812
Author(s):  
Mustaffa Bt Zahiraniza
Keyword(s):  
Carbon Steel ◽  
Regression Model ◽  
Least Squares ◽  
Multivariate Regression ◽  
Least Squares Method ◽  
Carbon Steels ◽  
Multivariate Regression Model ◽  
Offshore Pipelines ◽  
Corrosion Defect

This paper presents a probabilistic methodology in evaluating corrosion defect characteristics of carbon steels offshore pipelines. A nonlinear multivariate regression model was selected to describe the correlation among corrosion defect parameters while the least-squares method was used to minimize its residuals. The proposed framework were able to provide better insights on the degree of correlations among corrosion defect parameters, which eventually proven that the interactions among defects are indeed significant.

scholarly journals Asymptotic normality of a simple linear EV regression model with martingale difference errors

Filomat ◽  
2014 ◽  
Vol 28 (9) ◽  
pp. 1817-1825
Author(s):  
Guo-Liang Fan ◽  
Tian-Heng Chen
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Measurement Errors ◽  
Least Squares Method ◽  
Error Variance ◽  
Martingale Difference ◽  
Errors In Variables ◽  
Ev Regression Model ◽  
Biased Estimators ◽  
Better Than

This paper considers the estimation of a linear EV (errors-in-variables) regression model under martingale difference errors. The usual least squares estimations lead to biased estimators of the unknown parametric when measurement errors are ignored. By correcting the attenuation we propose a modified least squares estimator for a parametric component and construct the estimators of another parameter component and error variance. The asymptotic normalities are also obtained for these estimators. The simulation study indicates that the modified least squares method performs better than the usual least squares method.

Study on Forecasting of Gold Price Based on Varying-Coefficient Regression Model

2011 ◽  
Vol 467-469 ◽  
pp. 1398-1403
Author(s):  
Qi Zhang ◽  
Jun Hai Ma ◽  
Yan Wang
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Cross Validation ◽  
Least Squares Method ◽  
Weighting Function ◽  
Weighted Least Squares ◽  
Gold Price ◽  
Varying Coefficient ◽  
Sample Data ◽  
Varying Coefficient Regression

U.S. dollar index, oil prices, silver prices, DOW index, OECD leading index and the CRB index are selected and varying-coefficient regression model which has dynamic response to the various variables influence is applied to predict the gold price and improve the prediction accuracy in this paper. In addition, the weighted least squares is adopted as an estimation of the parameters, corrects the traditional least squares method defect which assumes the sample data weights equal points to the prediction, making sample weights larger closer with prediction points. In the choice of weighting function, the paper uses cross validation to gain smoothing parameter. In the last, we predicted the 12 months gold prices from January 2010 December 2010 applies varying-coefficient regression model.

‘Least squares’ method—theorem or law?

1980 ◽  
Vol 59 (9) ◽  
pp. 8
Author(s):  
D.E. Turnbull
Keyword(s):  
Least Squares ◽  
Least Squares Method
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