On the applicability of several conventional regression models for the estimation of solar global radiation component in Cameroon and Senegal sub-Saharan tropical regions

2016 ◽  
Vol 8 (2) ◽  
pp. 025906 ◽  
Author(s):  
Edouard Mboumboue ◽  
Donatien Njomo ◽  
Mamadou Lamine Ndiaye ◽  
Pape Alioune N'diaye ◽  
Mouhamadou Falilou Ndiaye ◽  
...  
Keyword(s):  
Regression Models ◽  
Global Radiation ◽  
Tropical Regions ◽  
Radiation Component ◽  
Sub Saharan ◽  
Solar Global Radiation ◽  
Conventional Regression

Improved Accuracy Models For Hourly Diffuse Solar Radiation

2005 ◽  
Vol 128 (1) ◽  
pp. 104-117 ◽  
Author(s):  
T. Muneer ◽  
S. Munawwar
Keyword(s):  
Solar Radiation ◽  
Regression Models ◽  
Global Radiation ◽  
Diffuse Radiation ◽  
Evaluation Procedure ◽  
Accuracy Score ◽  
Error Statistics ◽  
Diffuse Solar Radiation ◽  
Energy Applications ◽  
Extensive Evaluation

Solar energy applications require readily available, site-oriented, and long-term solar data. However, the frequent unavailability of diffuse irradiation, in contrast to its need, has led to the evolution of various regression models to predict it from the more commonly available data. Estimating the diffuse component from global radiation is one such technique. The present work focuses on improvement in the accuracy of the models for predicting horizontal diffuse irradiation using hourly solar radiation database from nine sites across the globe. The influence of sunshine fraction, cloud cover, and air mass on estimation of diffuse radiation is investigated. Inclusion of these along with hourly clearness index, leads to the development of a series of models for each site. Estimated values of hourly diffuse radiation are compared with measured values in terms of error statistics and indicators like, R2, mean bias deviation, root mean square deviation, skewness, and kurtosis. A new method called “the accuracy score system” is devised to assess the effect on accuracy with subsequent addition of each parameter and increase in complexity of equation. After an extensive evaluation procedure, extricate but adequate models are recommended as optimum for each of the nine sites. These models were found to be site dependent but the model types were fairly consistent for neighboring stations or locations with similar climates. Also, this study reveals a significant improvement from the conventional k-kt regression models to the presently proposed models.

scholarly journals Analysis of HIV/AIDS Epidemic and Socioeconomic Factors in Sub-Saharan Africa

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1230 ◽  
Author(s):  
Shuman Sun ◽  
Zhiming Li ◽  
Huiguo Zhang ◽  
Haijun Jiang ◽  
Xijian Hu
Keyword(s):  
Socioeconomic Factors ◽  
Regression Models ◽  
Sub Saharan Africa ◽  
Likelihood Method ◽  
Unknown Parameters ◽  
Aids Epidemic ◽  
Acquired Immunodeficiency ◽  
Sub Saharan ◽  
Immunodeficiency Syndrome ◽  
Hiv Aids

Sub-Saharan Africa has been the epicenter of the outbreak since the spread of acquired immunodeficiency syndrome (AIDS) began to be prevalent. This article proposes several regression models to investigate the relationships between the HIV/AIDS epidemic and socioeconomic factors (the gross domestic product per capita, and population density) in ten countries of Sub-Saharan Africa, for 2011–2016. The maximum likelihood method was used to estimate the unknown parameters of these models along with the Newton–Raphson procedure and Fisher scoring algorithm. Comparing these regression models, there exist significant spatiotemporal non-stationarity and auto-correlations between the HIV/AIDS epidemic and two socioeconomic factors. Based on the empirical results, we suggest that the geographically and temporally weighted Poisson autoregressive (GTWPAR) model is more suitable than other models, and has the better fitting results.

scholarly journals Exploring retailer marketing strategies for value added bean products in Kenya

2019 ◽  
Vol 22 (5) ◽  
pp. 675-687
Author(s):  
Florence Nakazi ◽  
Immaculate Babirye ◽  
Eliud Birachi ◽  
Michael Adrogu Ugen
Keyword(s):  
Marketing Strategy ◽  
Regression Models ◽  
Information Sources ◽  
Value Added ◽  
Market Value ◽  
Marketing Strategies ◽  
African Countries ◽  
Sub Saharan ◽  
Market Value Added ◽  
Using Data

Unlike many other Sub-Saharan African countries, for many years Kenya had comparative advantages in the manufacturing of processed bean products. However, for new competitors intending to join the bean processing industry, little is known about marketing strategies for value added bean products. Using data from 90 retailers in the Nairobi and Kiambu counties in Kenya, a two-step econometric procedure-multivariate probit and Poisson regression models were applied to analyse retailers’ marketing strategy decisions. Findings show that information sources, cost of marketing, supply modalities, price of products, and quantities handled significantly influenced retailers’ marketing strategy choice. Surveyed retailers applied varying marketing strategies to market value added bean products. There is need for prospective retailers to choose an appropriate mix of strategies to penetrate the dynamic market with a number of value added bean products, and promote local consumption of value added bean products.

Solar global radiation and climate at Genova, Italy

1981 ◽  
Vol 29 (1-2) ◽  
pp. 129-135 ◽  
Author(s):  
A. Elena ◽  
G. Flocchini ◽  
V. Pasquale
Keyword(s):  
Global Radiation ◽  
Solar Global Radiation

Simulation on Solar Energy Collection to Power a Thermoacoustic Prime Mover Using Pressurized Hot Steam

2011 ◽  
Author(s):  
Ikhsan Setiawan ◽  
Makoto Nohtomi ◽  
Masafumi Katsuta
Keyword(s):  
Solar Energy ◽  
Global Radiation ◽  
Average Energy ◽  
Steam Pressure ◽  
Fresnel Lens ◽  
Water Volume ◽  
Prime Mover ◽  
Simple Simulation ◽  
Solar Global Radiation ◽  
Yogyakarta City

It has been performed a simple simulation and calculation on solar energy collection which is used indirectly to power a thermoacoustic prime mover by producing pressurized hot steam which would supply thermal energy to the prime mover via sealed-off hot heat exchangers. The solar energy collection took place in Yogyakarta City - Indonesia where the average energy of solar global radiation of 4.8 kWh/m2/day (17.3MJ/m2/day) is available around the year. The calculation including the amount of the remaining heat stored, steam pressure, and steam temperature for various areas of the collector unit (Fresnel lens) and volume of water, were done as a function of time for several days. We found that appropriate combinations of lens area and water volume would enable us to operate the thermoacoustic prime mover continuously all day and night.

scholarly journals Forecast Bitcoin Volatility with Least Squares Model Averaging

Econometrics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 40 ◽  
Author(s):  
Tian Xie
Keyword(s):  
Least Squares ◽  
Regression Models ◽  
Model Averaging ◽  
Realized Volatility ◽  
Model Specification ◽  
Asset Market ◽  
Averaging Methods ◽  
Empirical Results ◽  
Conventional Regression

In this paper, we study forecasting problems of Bitcoin-realized volatility computed on data from the largest crypto exchange—Binance. Given the unique features of the crypto asset market, we find that conventional regression models exhibit strong model specification uncertainty. To circumvent this issue, we suggest using least squares model-averaging methods to model and forecast Bitcoin volatility. The empirical results demonstrate that least squares model-averaging methods in general outperform many other conventional regression models that ignore specification uncertainty.

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