Generalized categorical regression model for size reduction of multiple biomass and grinders

2016 ◽  
2021 ◽  
Author(s):  
Mohamad Khoirun Najib ◽  
Sri Nurdiati ◽  
Ardhasena Sopaheluwakan

Abstract The copula-based joint distribution can construct a fire risk model to improve forest fires' early warning system, especially in Kalimantan. In this study, we model and analyze the copula-based joint distribution between climate conditions and hotspots. We used several climate conditions, such as total precipitation, dry spells, and El Nino-Southern Oscillation (ENSO). We used copula functions with sample size reduction to construct the joint distributions and the copula regression model to estimate the fire size. The results show that the probability of extreme hotspots number during normal ENSO conditions is very rare and almost near zero during La Nina. Other than that, extreme hotspot event (more severe than in 2019) during El Nino is more sensitive to total precipitation than dry spells based on the conditional survival function. However, the copula regression model found that the model used dry spells as a climate condition better than total precipitation. In this model, the 95% confidence interval of the expected hotspots can cover all actual hotspots data.


2014 ◽  
Vol 12 (1) ◽  
pp. 671-682
Author(s):  
Simon Radipere

The study examined relationship between self-efficacy and business performance using 500 SMMEs in Gauteng province, South Africa. Questionnaire was used to collect data from 500 SMMEs owners. The findings from the survey were modelled through a categorical regression model with business performance as dependent variable. The level of significance of the fourteen variables out of eighteen variables suggests that self-efficacy be classified as the strongest predictor of business performance. These findings, depicting the magnitude of the business environment in the study area, clearly confirm the positive impact of self-efficacy on business performance


2020 ◽  
Author(s):  
Gaojing Qu ◽  
Guoxin Huang ◽  
Meiling Zhang ◽  
Hui Yu ◽  
Xiaoming Song ◽  
...  

AbstractBackgroundTo characterize C-reactive protein (CRP) changes features from patients with coronavirus disease 2019 (COVID-19) and to quantify the correlation between CRP value and clinical classification.MethodsThis was a bidirectional observational cohort study. All laboratory confirmed COVID-19 patients hospitalized in Xiangyang No.1 People’s Hospital were included. Patients’ general information, clinical type, CRP value and outcome were collected. Patients were grouped according to the age, clinical type and outcome, and their CRP were compared. The CRP value, age gender, and clinical type were used to build a categorical regression model to investigate the association between CRP and clinical type.ResultsThe 131 patients aged 50.13±17.13 years old. There were 4 mild, 88 moderate, 21 severe and 18 critical cases. Statistical significance of CRP median exists between different clinical types and ages. There were 10 deaths and 121 cases have been discharged. The CRP in death group dramatically increased continuously until died, while increased firstly and decreased later in the survivor and survivor in critical type. The categorical regression model also showed that CRP and age had significant coefficient. During the first 15 days from symptom onset, the maximum of CRP ranged between 0.47-53.37 mg/L were related to mild combined with moderate type, ranged 53.84-107.08 mg/L were related to severe type, and 107.42-150.00 mg/L were related to the critical type.ConclusionsCRP showed different distribution feature and existed differences in various ages, clinical types and outcomes of COVID-19 patients. The features corresponded with disease progression.


2015 ◽  
Vol 13 (1) ◽  
pp. 205-213
Author(s):  
Simon Radipere

The study examined relationship between business support and business performance using 500 SMMEs in Gauteng province, South Africa. Questionnaire was used to collect data from 500 SMMEs owners. The findings from the survey were modelled through a categorical regression model with business performance as dependent variable. The level of significance of the four variables out of eight variables suggests that business support be classified as the strongest predictor of business performance.


2021 ◽  
Vol 12 (1) ◽  
pp. 204
Author(s):  
Ilir Kapaj ◽  
Albana Gjoni ◽  
Sadik Maloku ◽  
Ana Mane Kapaj

The increasing trend of wine consumption in Albania has led the development of the respective subsectors, viticulture and the wine industry. In the order for the domestic wine production industry to be competitive, a detailed understanding of the consumer’s buying behavior is a prerequisite. To this end, this study offers an actual perspective of the consumption behavior of wine customers in Tirana region. One of the goals of this paper is to identify and quantify determinants of wine consumption by using a regression model called “Categorical Regression Estimation” for non-numeric response variables. A questionnaire has been designed for this purpose, which is based on the literature but also on the recognition of the customer profile in the country, considering several socio-economic factors. Through 230 face-to-face interviews, the aim is to evaluate the impact on wine consumption of income, age, education, religion, nutrition culture, wine prices, wine origin as well as other socio-demographic factors related to the profile of the consumer. The analysis and interpretation of the results reveal interesting factors that determine the wine consumption. Age, education, income level and price of the wine are the main factors affecting the consumer decision to buy wine. Older people (over 40 years old) represent 1.4 times higher willingness to buy wine relatively to the younger people. Meanwhile, among people with higher income level chances that they will buy wine are 2.15 higher relatively to the people with lower monthly income level. From the results appears that education have positive impact on wine consumption while gender does not represent a significant difference.


2018 ◽  
Vol 1 (1) ◽  
pp. 52 ◽  
Author(s):  
Mohamed Tareq Hossain ◽  
Zubair Hassan ◽  
Sumaiya Shafiq ◽  
Abdul Basit

This study investigates the impact of Ease of Doing Business on Inward FDI over the period from 2011 to 2015 across the globe. This study measures ease of doing business using starting a business, getting credit, registering property, paying taxes and enforcing contracts. The research used a sample of 177 countries from 190 countries listed in World Bank. Least square regression model via E-views software used to examine causal relationship. The study found that ease of doing business indicators ‘Enforcing Contracts’ was found to have a positive significant impact on Inward FDI. Nevertheless, ‘Getting Credit’ and ‘Registering Property’ were found to have a negative significant impact on Inward FDI. However, ‘Starting a Business’ and ‘Paying Taxes’ have no significant impact on Inward FDI in the studied timeframe of this research. The findings of the study suggested the ease of doing business enables inward FDI through better contract enforcements, getting credit and registering property. The findings of the research will assist international managers and companies to know the importance of ease of doing business when investing in foreign countries through FDI.


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