Time Series Analysis of New Cars Sale in Bosnia and Herzegovina

2015 ◽  
Vol 806 ◽  
pp. 287-293
Author(s):  
Esad Jakupović ◽  
Vladimir Stojanović ◽  
Sanel Jakupović ◽  
Dragana Trnavac
Keyword(s):  
Time Series ◽  
Bosnia And Herzegovina ◽  
Polynomial Regression ◽  
Growth Index ◽  
Coefficient Of Determination ◽  
Chain Growth ◽  
Degree Polynomial ◽  
Car Sales ◽  
The Given ◽  
Polynomial Regression Model

The paper provides analysis of new car sales in Bosnia and Herzegovina for the period 2007-2014. For the examined period new car sales in B&H was reduced by 53.67%, from 12449 in 2007 to 6682 in 2014. The trend can be approximated using 3rd degree polynomial regression model with coefficient of determination R2=0,845. Most new cars sold were by Skoda and least was sold by Porsche. Total number of sold vehicles for this period was 73152. We also present annual growth, chain growth and cumulative growth index for the given period.

scholarly journals REGIONAL DETERMINANTS OF THE EXPANSION OF COVID-19 IN BRAZIL

2020 ◽  
Author(s):  
Waldecy Rodrigues ◽  
David Nadler Prata ◽  
Wainesten Camargo
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Temperature Variation ◽  
Regional Differences ◽  
Polynomial Regression ◽  
Climatic Factors ◽  
Demographic Factors ◽  
Relative Effect ◽  
City Population ◽  
Polynomial Regression Model

ABSTRACTObjectiveThis study investigates the regional differences in the occurrence of COVID-19 in Brazil and its relationship with climatic and demographic factors by use data from February 26 to April 04, 2020. Methods: A Polynomial Regression Model with cubic adjustments of the number of days of contagion, demographic density, city population and climatic factors was designed and used to explain the spread of COVID-19 in Brazil.Main resultsIt was evidenced that temperature variation maintains a relationship with the reduction in the number of cases of COVID-19. A variation -3.4% in the number of COVID-19 cases was found for each increase of 1 ° C.ConclusionThere are evidences that the temperature, has a relative effect in the variation in the number of COVID-19’s researched cases. For the reason, it recommends this relationship deserves to be investigated in other tests with more extended time series, wide and with especially non-linear data adjustments.

scholarly journals Prediction of Delivered Quantities of Drinking Water and Discharged Wastewater of the Nišava District (Serbia)

2020 ◽  
Vol 8 (E) ◽  
pp. 664-669
Author(s):  
Nina Pavićević
Keyword(s):  
Drinking Water ◽  
Linear Regression ◽  
Regression Model ◽  
Trend Analysis ◽  
Regression Models ◽  
Polynomial Regression ◽  
Quadratic Regression ◽  
Degree Polynomial ◽  
Basic Substance ◽  
Polynomial Regression Model

Water, as a natural resource, is the most basic substance of life that has immeasurable significance for the living world, ecosystems, and planet earth. In this paper, a prediction of delivered quantities of drinking water (DQDW) and total discharged wastewater (TDWW) of the Nišava district (Serbia) for the period 2019-2023 is given. The prediction for DQDW for the period 2019-2023 was made based on linear regression model, quadratic regression model, and cubic regression model according to which the data on DQDW of the Nišava district (Serbia) for the period 2006-2018 were approximated. The prediction for TDWW for the period 2019–2023 was done based on the 4th-degree polynomial regression model, the 5th-degree polynomial regression model, and the 6th-degree polynomial regression model by which the DQDW data were approximated of the Nišava district (Serbia) for the period 2006–2018. The presented prediction is a continuation of the paper “Trend analysis of total affected water and total discharged wastewater of the Nišava district (Serbia)” by the same author, in which for data on DQDW and TDWW of the Nišava district (Serbia) for the period 2006–2018 trend analysis and selected regression models have been shown.

Development and evaluation of trans-Amadi groundwater parameters: The integration of finite element techniques

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Finite Element ◽  
Polynomial Regression ◽  
Nitrate Concentration ◽  
Strong Relationship ◽  
Total Iron ◽  
Coefficient Of Determination ◽  
Port Harcourt ◽  
Polynomial Expression ◽  
The Relationship ◽  
Best Fit

Mathematical model was developed and evaluated to monitor and predict the groundwater characteristics of Trans-amadi region in Port Harcourt City. In this research three major components were considered such as chloride, total iron and nitrate concentration as well as the polynomial expression on the behavious on the concentration of each component was determined in terms of the equation of the best fit as well as the square root of the curve. The relationship between nitrate and distance traveled by Nitrate concentration by the model is given as Pc = 0.003x2 - 0.451x + 14.91with coefficient of determination, R² = 0.947, Chloride given as Pc = 0.000x2 - 0.071x + 2.343, R² = 0.951while that of Total Iron is given as Pc = 2E-05x2 - 0.003x + 0.110, R² = 0.930. All these show a strong relationship as established by Polynomial Regression Model. The finite element techniques are found useful in monitoring, predicting and simulating groundwater characteristics of Trans-amadi as well as the prediction on the variation on the parameters of groundwater with variation in time.

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals Fetal Biparietal Diameter and Abdominal Circumference Ratio in Bangladesh

1970 ◽  
Vol 39 (1) ◽  
pp. 24-27
Author(s):  
Sabrina Q Rashid
Keyword(s):  
Polynomial Regression ◽  
Cross Sectional Study ◽  
Abdominal Circumference ◽  
Accurate Assessment ◽  
Sectional Study ◽  
Cross Sectional ◽  
Biparietal Diameter ◽  
First Time ◽  
Polynomial Regression Model ◽  
Growth Abnormality

This study was conducted to determine fetal biparietal diameter and abdominal circumference ratio in Bangladesh. There is still no table of this ratio in our country. A prospective, cross-sectional study was conducted on well dated, singleton fetuses of healthy pregnant women. One table and two graphs were prepared by fitting Polynomial regression model. Percentiles, mean and two standard deviations were derived of the ratio. Fetal charts of the raw data with superimposed fitted curves were constructed. The model showed a good fit to the data of 1223 subjects. It covered 95% of the population and gave 3rd, 10th, 50th, 90th and 97th percentiles. This chart can be useful for accurate assessment of fetal biparietal diameter and abdominal circumference ratio to determine the type of fetal growth abnormality, symmetrical or asymmetrical. This is the first time that this ratio has been studied in Bangladesh. Key words: Biparietal diameter; abdominal circumference. DOI: 10.3329/bmj.v39i1.6229 Bangladesh Medical Journal 2010; 39(1): 24-27

scholarly journals Photostability study of amlodipine besylate tablets packed in primary packaging

2021 ◽  
Vol 10 (1) ◽  
pp. 20-28
Author(s):  
Ivana Savić-Gajić ◽  
Ivan Savić ◽  
Predrag Sibinović ◽  
Valentina Marinković
Keyword(s):  
Mobile Phase ◽  
Limit Of Detection ◽  
Degradation Products ◽  
Hplc Method ◽  
Coefficient Of Determination ◽  
Amlodipine Besylate ◽  
Limit Of Quantification ◽  
First Order Kinetics ◽  
The Given

In this study, the modified stability-indicating RP-HPLC method was validated for quantitative analysis of amlodipine besylate in the presence of its impurity D (3-ethyl 5-methyl 2-[(2-aminoethoxy)methyl]-4-(2-chlorophenyl)-6-methylpyridine-3,5-dicarboxylate). The method was applied for the determination of an analyte in the tablets and irradiated samples packed in the primary packaging (Alu/PVC/PVDC blister packaging). The efficient chromatographic separation was achieved using a ZORBAX Eclipse XDB-C18 column (4.6×250 mm, 5 mm) with isocratic elution of mobile phase which consisted of acetonitrile:methanol:triethylamine solution (15:35:50, v/v/v) (pH 3.0). The flow rate of the mobile phase was 1 mL min-1, while the detection of amlodipine besylate was carried out at 273 nm. Amlodipine besylate and its impurity D were identified at the retention times of 16.529 min and 2.575 min, respectively. The linearity of the method with the coefficient of determination of 0.999 was confirmed in the concentration range of 10 - 75 µg mL-1 for amlodipine besylate. The limit of detection was 0.2 µg mL-1, while the limit of quantification was 0.66 µg mL-1. After UV and Vis radiation of the tablets packed in the primary packaging, the content of amlodipine besylate was reduced by 22.38% and 19.89%, respectively. The presence of new degradation products was not detected under the given chromatographic conditions. The photodegradation of amlodipine besylate followed pseudo-first-order kinetics. Based on the half-life of amlodipine besylate (38.4 days for UV radiation and 43.3 days for Vis radiation), it was concluded that amlodipine besylate in the tablets has satisfactory photostability after its packing in the Alu/PVC/PVDC blister packaging.

scholarly journals Polynomial Regression Model Analysis of Abdominal Wall Tension and Intra-abdominal Pressure in Critically ill Patients

2021 ◽  
Author(s):  
Hao Tang ◽  
Dongchu Zhao ◽  
Chuan Zhang ◽  
Xiaoying Huang ◽  
Dong Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Polynomial Regression ◽  
Prognostic Indicators ◽  
Wall Tension ◽  
Abdominal Hypertension ◽  
Abdominal Compliance ◽  
Polynomial Regression Model

Abstract BackgroundAbdominal wall tension (AWT) plays an important role in the pathogenesis of abdominal compliance (AC). This study uses a polynomial regression model to analyze the correlation between intra-vesical pressure(IVP) and AWT in critically ill patients and provides new ideas for the diagnosis and treatment of critically ill patients with intra-abdominal hypertension（IAH）.MethodsA retrospective analysis was conducted in critically ill patients who met the inclusion criteria and were admitted to the Department of intensive care unit of Daping Hospital of Army Medical University from March 14, 2019, to May 23, 2020. According to the IVP on the first day of ICU admission and death within 28 days, the patients were divided into the IAH group (IVP ≥12 mmHg), the non-IAH group, the survival group and the nonsurvival group. The demographic and clinical data, prognostic indicators, AWT and IVP on days 1-7 after entering the ICU, IAH risk factors, and 28-day death risk factors were collected.ResultsA total of 100 patients were enrolled, with an average age of 45.59±11.4 years. There were 55 males (55%), 30 patients from departments of internal medicine (30%), 43 patients from surgery departments (43%), and 27 trauma patients (27%). In the IAH group, there were 50 patients (29 males, 58%), with an average age of 45.28±12.27 years; there were 50 patients (26 males, 52%) in the non-IAH group, with an average age of 45.90±10.58 years. The IVP on the 1st day and the average IVP within 7 days of the IAH group was 18.99（17.52，20.77）mmHg and 19.43（16.87，22.25）mmHg, respectively, which was higher than that of the non-IAH group [ 6.14（3.48，8.70）mmHg, 6.66（2.74，9.08）mmHg], p＜0.001. The AWT on the 1st day and the average AWT within 7 days of the IAH group was 2.89±0.32 N/mm and 2.82±0.46 N/mm, respectively, which was higher than that of the non-IAH group [(2.45±0.29)N/mm,(2.43±0.39)N/mm],p＜0.001.The polynomial regression models showed that the average AWT and IVP on the 1st day and within 7 days were AWTday1 = -2.450×10-3IVP2+9.695×10-2 IVP+2.046，r=0.667（p＜0.0001），and AWTmean = -2.293×10-3IVP2+9.273×10-2 IVP+2.081, respectively. The logistic regression analysis showed that AWTday1 of 2.73-2.97 N/mm increased the patient's 28-day mortality risk (OR: 6.834; 95%: 1.105-42.266, p=0.010).ConclusionsThere is a nonlinear correlation between AWT and IVP in critically ill patients, and a high AWT may indicate poor prognosis.

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