Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

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ANÁLISE DA RELAÇÃO ENTRE O3, NO E NO2 USANDO TÉCNICAS DE REGRESSÃO LINEAR MÚLTIPLA

GEOgraphia ◽

10.22409/geographia2018.v20i43.a27215 ◽

2018 ◽

Vol 20 (43) ◽

pp. 124 ◽

Cited By ~ 1

Author(s):

Amaury De Souza ◽

Priscilla V Ikefuti ◽

Ana Paula Garcia ◽

Debora A.S Santos ◽

Soetania Oliveira

Keyword(s):

Time Series ◽

Linear Regression ◽

Nitrogen Dioxide ◽

Multiple Linear Regression ◽

Quality Parameters ◽

Environmental Pollutant ◽

Environmental Research ◽

Linear Regression Models ◽

Mato Grosso ◽

The Impact

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Flood Forecasting and Uncertainty Assessment Using Wavelet- and Bootstrap-Based Neural Networks

Advances in Computational Intelligence and Robotics - Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering ◽

10.4018/978-1-5225-4766-2.ch004 ◽

2018 ◽

pp. 74-93

Author(s):

Mukesh Kumar Tiwari ◽

Chandranath Chatterjee

Keyword(s):

Neural Networks ◽

Time Series ◽

Linear Regression ◽

Multiple Linear Regression ◽

Flood Control ◽

Time Series Data ◽

Flood Forecasting ◽

Performance Comparison ◽

Linear Regression Models ◽

Original Time

Accurate and reliable forecasting of flood is inevitable for flood control planning and rehabilitation. There are several models available for flood forecasting, but as far as accuracy, reliability, and data scarcity are concerned, soft computing techniques (e.g., artificial neural networks) have been found to achieve the target. A wavelet-, bootstrap-, and neural-network-based framework (BWANN) is presented here for flood forecasting. Performance comparison of the proposed BWANN model is presented with wavelet-based ANN (WANN), wavelet-based MLR (WMLR), bootstrap- and wavelet-analysis-based multiple linear regression models (BWMLR), traditional ANN, and traditional multiple linear regression (MLR) models for flood forecasting. For development of WANN models, original time series data is decomposed using wavelet transformation, and wavelet sub-time series are considered to develop WANN model. A comparative analysis is carried out among different approaches of WANN model development using wavelet sub-time series.

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La incidencia de la asistencia técnica en el desempeño de las unidades productoras agropecuarias en Colombia: un análisis comparativo

Ad-gnosis ◽

10.21803/adgnosis.9.9.438 ◽

2020 ◽

Vol 9 (9) ◽

pp. 68-81

Author(s):

Carlos A Rodríguez Arias ◽

◽

Edwin Javier Arriera Valderrama ◽

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Agricultural Production ◽

Regression Models ◽

Technical Assistance ◽

Regional Level ◽

Linear Regression Models ◽

Assistance Programs ◽

The Impact ◽

Multiple Linear Regression Models

The technical assistance programs have the purpose of transferring knowledge to the Agricultural Production Units -UPA- for their efficient development. However, this knowledge transfer in many cases is not effective, having little influence on the UPAS. In this sense, this article aims to assess the impact that technical assistance programs have had on the performance of UPAs at the regional level by making comparisons between regions. Through multiple linear regression models, the degree of influence of different technical assistance programs on the performance of agricultural production units will be established. The results show that in general these programs have had little impact on the performance of the UPA for each region analyzed.

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PENGARUH KUALITAS PELAYANAN DAN KEPERCAYAAN TERHADAP LOYALITAS NASABAH PT BANK MANDIRI,Tbk CABANG JAKARTA KELAPA GADING BARAT

Jurnal Manajemen Bisnis Krisnadwipayana ◽

10.35137/jmbk.v3i3.11 ◽

2015 ◽

Vol 3 (3) ◽

Author(s):

Imam Wibowo ◽

Santi Putri Ananda

Keyword(s):

Linear Regression ◽

Service Quality ◽

Multiple Linear Regression ◽

Analysis Tool ◽

Positive Contribution ◽

Homogeneous Population ◽

Independent Variables ◽

Research Population ◽

The Impact

Purpose-To study the impact of the service quality and trust on customers loyalty of PT.Bank Mandiri,Tbk; Kelapa Gading Barat Branch. To improve the customers loyalty there are several factors that can influence them, such as service quality and trust. Methodology/approach-The research population was all customers PT.Bank Mandiri,Tbk;Kelapa Gading Barat Branch.According to the homogeneous population and based on the Gay and Diehl Theory, the samples taken were 50 people. Variables in this investigations consisted of: a).Independent Variables (exogenous): Service Quality (X1) and Trust (X2). b).The dependent variable (endogenous) Customers Loyalty (Y). Analysis tool being used is multiple linear regression which previously conducted validity and realiability. Findings-The result of investigations that service quality and trust simultaneously have a very strong contribution of 75,5% to the customers loyalty, and partially showed that service quality has significant and positive contribution to the customers loyalty of 64,8%. Partially, the trust variable has significant and positive contribution which amounted to 55,9% to the customers loyalty.

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FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

Journal of Business Economics ◽

10.35760/eb.2018.v23i1.1812 ◽

2018 ◽

Vol 23 (1) ◽

pp. 60-71

Author(s):

Wigiyanti Masodah

Keyword(s):

Interest Rate ◽

Linear Regression ◽

Interest Rates ◽

Regression Models ◽

Linear Regression Models ◽

Negative Impacts ◽

Main Activity ◽

The Impact ◽

The Given ◽

Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

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Multiple linear regression models for predicting the n‑octanol/water partition coefficients in the SAMPL7 blind challenge

Journal of Computer-Aided Molecular Design ◽

10.1007/s10822-021-00409-2 ◽

2021 ◽

Author(s):

Kenneth Lopez ◽

Silvana Pinheiro ◽

William J. Zamora

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Regression Models ◽

Partition Coefficients ◽

Linear Regression Models ◽

Blind Challenge ◽

Multiple Linear Regression Models

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Non-Parametric Generalized Additive Models as a Tool for Evaluating Policy Interventions

Mathematics ◽

10.3390/math9040299 ◽

2021 ◽

Vol 9 (4) ◽

pp. 299

Author(s):

Jaime Pinilla ◽

Miguel Negrín

Keyword(s):

Linear Regression ◽

Regression Models ◽

Linear Trend ◽

Generalized Additive Models ◽

Additive Models ◽

Linear Regression Models ◽

Non Linear ◽

Nonlinear Trends ◽

The Impact ◽

Non Parametric

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.

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A139 IMPROVED QUALITY OF LIFE AFTER ENDOSCOPIC THERAPY FOR BARRETT’S ESOPHAGUS AND EARLY ESOPHAGEAL CANCER IN SOUTHERN ALBERTA

Journal of the Canadian Association of Gastroenterology ◽

10.1093/jcag/gwab002.137 ◽

2021 ◽

Vol 4 (Supplement_1) ◽

pp. 125-126

Author(s):

T Jeyalingam ◽

M Woo ◽

S E Congly ◽

J David ◽

P J Belletrutti ◽

...

Keyword(s):

Quality Of Life ◽

Linear Regression ◽

Multiple Linear Regression ◽

Barrett’S Esophagus ◽

Barrett's Esophagus ◽

Endoscopic Therapy ◽

Negative Impact ◽

Older Age ◽

The Impact

Abstract Background In patients with Barrett’s esophagus (BE), endoscopic therapy reduces the risk of progression to invasive esophageal adenocarcinoma (EAC). Data on the impact of endoscopic therapy on patient quality of life (QoL) is limited. Aims We aimed to assess: (1) change in QoL during the course of endoscopic therapy for BE, (2) factors which predict this change, (3) whether achieving complete remission of dysplasia (CRD) or intestinal metaplasia (CRIM) affect the degree of change. Methods We conducted a retrospective observational study using a prospectively maintained database of BE patients treated in Calgary, Alberta from 2013–2020 containing data on demographics, BE disease characteristics and therapeutics, QoL, and follow-up. QoL was determined prior to initiation of therapy and after each treatment session using a validated questionnaire. Descriptive statistics were calculated and change in QoL was compared using a Wilcoxon signed ranks test. Backwards multiple linear regression analysis was performed to determine predictors of change in QoL. Results Of 130 BE patients, 112 (86.1%) were male and 104 (80%) had dysplastic histology or intramucosal carcinoma on index endoscopy. Mean (SD) age was 65.6 (12.0) years. At time of analysis, 76 patients (58.5%) had completed endoscopic therapy, of whom 69 (90.8%) achieved CRIM; 54 patients (41.5%) were still undergoing treatment. There was significant improvement in all QoL measures during the treatment course except for “depression” (Table 1). Patients with CRIM or CRD had reductions in “sleep difficulty” and “negative impact on life” to a significantly greater degree vs patients not achieving CRIM (Δ sleep -0.45 vs 0.0, P=0.002; Δ negative impact -0.4 vs -0.05, P=0.014) or CRD (Δ sleep -0.40 vs +0.60, P=0.002; Δ negative impact -0.40 vs +0.20, P=0.04). Multiple linear regression revealed older age (B=-0.03, P=0.008) and fewer number of EMR sessions (B=0.254, P=0.008) were correlated with greater improvement in QoL. Conclusions Endoscopic therapy improves QoL in BE patients, especially in those achieving CRIM/CRD. Older age and fewer EMRs are correlated with greater improvement in QoL. These results further reinforce the role of endoscopic therapy as the first line treatment of BE and early EAC. Funding Agencies None

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Isotonic quadriceps endurance is better associated with daily physical activity than quadriceps strength and power in COPD: an international multicentre cross-sectional trial

Scientific Reports ◽

10.1038/s41598-021-90758-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Erik Frykholm ◽

Sarah Gephine ◽

Didier Saey ◽

Arthur Lemson ◽

Peter Klijn ◽

...

Keyword(s):

Physical Activity ◽

Linear Regression ◽

Multiple Linear Regression ◽

Regression Models ◽

Sedentary Time ◽

Quadriceps Strength ◽

Linear Regression Models ◽

Cross Sectional ◽

Quadriceps Function ◽

Multiple Linear Regression Models

AbstractKnowledge about modifiable determinants of daily physical activity (PA) in patients with chronic obstructive pulmonary disease (COPD) is crucial to design effective PA interventions. The present study aimed to determine the contribution of quadriceps strength, power and endurance to daily PA in COPD. Additionally, for quadriceps endurance, we also aimed to determine to what extent the association varies according to the mode of movement (isotonic, isometric, or isokinetic). Using a multicentre cross-sectional trial design we determined the contribution of quadriceps function to daily PA (steps, sedentary time and time spent doing moderate-to-very-vigorous physical activity [MVPA]) using bivariate and partial Pearson correlation analysis (r) and multiple linear regression models (ΔR2). Pre-determined controlling factors were sex, age, body mass index (BMI), COPD-assessment test, forced expiratory volume in one second in percent of the predicted value (FEV1pred), and distance walked on the 6-minute walk test. Eighty-one patients with COPD (mean ± SD: age 67 ± 8 years, FEV1pred 57 ± 19%, daily steps 4968 ± 3319, daily sedentary time 1016 ± 305 min, and MVPA time 83 ± 45 min) were included. Small to moderate bivariate correlations (r = .225 to .452, p < .05) were found between quadriceps function and measures of PA. The best multiple linear regression models explained 38–49% of the variance in the data. Isotonic endurance was the only muscle contributor that improved all PA models; daily steps (ΔR2 = .04 [relative improvement 13%] p = .026), daily sedentary time (ΔR2 = .07 [23%], p = .005) and MVPA-minutes (ΔR2 = .08 [20%], p = .001). Isotonic endurance was also independently associated with most PA variables, even when controlling for strength, power or isometric-isokinetic endurance properties of the muscle (r = .246 to .384, p < .05). In contrast, neither strength, power, isometric-or isokinetic endurance properties of the muscle was independently associated with PA measures when controlling for isotonic endurance (r = .037 to .219, p > .05). To conclude, strength, power, and endurance properties of the quadriceps were low to moderately associated with PA in patients with COPD. Isotonic quadriceps endurance was the only quadriceps property that was independently associated with the different measures of PA after controlling for a basic set of known determinants of PA, quadriceps strength or power, or isometric or isokinetic quadriceps endurance. Future longitudinal studies should investigate its potential as a modifiable determinant of PA.

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