scholarly journals Quantifying the Impact of Linear Regression Model in Deriving Bio-Optical Relationships: The Implications on Ocean Carbon Estimations

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3032 ◽  
Author(s):  
Bellacicco ◽  
Vellucci ◽  
Scardi ◽  
Barbieux ◽  
Marullo ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Type I ◽  
Ocean Colour ◽  
Data Set ◽  
Argo Floats ◽  
In Situ Data ◽  
Carbon Biomass ◽  
The Impact

Linear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g., Biogeochemical Argo floats; BGC-Argo floats) and satellite ocean colour sensors (e.g., SeaWiFS, VIIRS, OLCI). However, different methods can be applied to a given pair of variables to determine the coefficients of the linear equation fitting the data, which are therefore not unique. In this work, we quantify the impact of the choice of “regression method” (i.e., either type-I or type-II) to derive bio-optical relationships, both from theoretical perspectives and by using specific examples. We have applied usual regression methods to an in situ data set of particulate organic carbon (POC), total chlorophyll-a (TChla), optical particulate backscattering coefficient (bbp), and 19 years of monthly TChla and bbp ocean colour data. Results of the regression analysis have been used to calculate phytoplankton carbon biomass (Cphyto) and POC from: i) BGC-Argo float observations; ii) oceanographic cruises, and iii) satellite data. These applications enable highlighting the differences in Cphyto and POC estimates relative to the choice of the method. An analysis of the statistical properties of the dataset and a detailed description of the hypothesis of the work drive the selection of the linear regression method

scholarly journals Religiosity and Halal Certification: Its Effect on Interest in Buying Traditional Food

2022 ◽  
Vol 6 (2) ◽  
pp. 79
Author(s):  
Najmudin Najmudin ◽  
Syihabudin Syihabudin
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Research Method ◽  
Quantitative Methods ◽  
Regression Method ◽  
Linear Regression Method ◽  
Traditional Food ◽  
Questionnaire Data ◽  
Multiple Linear Regression Method ◽  
The Impact

This study aims to determine (1)—the influence of religiosity on the interest in buying traditional food of sate bandeng. (2). The effect of halal certification on the interest in buying traditional food of sate bandeng. And (3). The impact of religiosity and halal certification on interest in buying traditional food of sate bandeng. This research is the millennial consumers of traditional food of Sate Bandeng Kang Cepi Kaujon, Serang City, Banten Province. The research method used is quantitative. Methods of data collection using a questionnaire. Data were processed using SPSS version 23 software. Data analysis used the multiple linear regression method. The results of this study indicate that (1). Religiosity affects an interest in buying traditional food of Sate Bandeng. (2). Halal certification affects an interest in buying traditional food of sate bandeng (3). Religiosity and halal certification have a positive and significant impact on interest in buying traditional food of Sate Bandeng. Consumers’ interest in buying traditional food of Sate Bandeng is influenced by religiosity and halal certification as much as 48.8 percent. In comparison, the remaining 51.2 percent is influenced by other variables not examined in this study.

scholarly journals Impact of Delay on Cost Overrun in Construction Projects in Algeria

2019 ◽  
Vol 5 (2) ◽  
pp. 25
Author(s):  
Salhi Roumeissa
Keyword(s):  
Linear Regression ◽  
Construction Projects ◽  
Project Success ◽  
Regression Method ◽  
Linear Regression Method ◽  
Cost Overrun ◽  
Simple Linear Regression ◽  
Schedule Delay ◽  
Proposed Model ◽  
The Impact

Project success is the ultimate goal of the various project stackeholders (Salhi.R 2018). Asuccessful project means that the project is completed on time, within the agreed budget and according to the contract specifications. Delay is one of the most reccuring problems in construction project in Algeria, and it is considered as the main cause of cost overrun, time overrun, disput and claims.The objective of this paper is to mesure the impact of schedule delay on cost overrun, using the simple linear regression method and the coefficient of correlation. The proposed model can be used by practitioners as predictive mesure to address possible cost overrun.

scholarly journals Uncertainty of Measurement in the Linear Regression Method Part 2. Uncertainty Bands of the Regression Straight-Line for the Correlated Data of Y Variable

2020 ◽  
Vol 24 (4) ◽  
pp. 61-72
Author(s):  
Zygmunt Warsza ◽  
Jacek Puchalski
Keyword(s):  
Linear Regression ◽  
Correlated Data ◽  
Regression Method ◽  
Linear Regression Method ◽  
Uncertainty Of Measurement ◽  
Relative Uncertainty ◽  
Type B ◽  
Straight Line ◽  
The Impact ◽  
Simple Regression

This is the continuation of authors’ works on the description of the accuracy of various straight-line cases determined from the results of linear regression measurements. In the first work, the essence, criteria and dependencies of the regression method were examined, as well as simulated examples of determining simple uncertainty bands fitted to measured points with uncorrelated ordinates. The GUM Guide was referred to and the B type uncertainty not discussed yet in the literature about the application of the regression method in measurements was taken into account. This work discusses determining the equation of a simple regression and its uncertainty bands from measuring points with ordinates with autocorrelation. This is illustrated by examples with precisely known abscissa and ordinates with different correlation variants, and absolute and relative uncertainty types A and B. Proposed is the extended method for assessing the accuracy of simple regression takes into account both the correlation of the Y variable data and the impact of type B uncertainty in routine measurements.

scholarly journals Impact of Delay on Cost Overrun in Construction Projects in Algeria

2019 ◽  
Vol 5 (2) ◽  
pp. 25
Author(s):  
Salhi Roumeissa
Keyword(s):  
Linear Regression ◽  
Construction Projects ◽  
Project Success ◽  
Regression Method ◽  
Linear Regression Method ◽  
Cost Overrun ◽  
Simple Linear Regression ◽  
Schedule Delay ◽  
Proposed Model ◽  
The Impact

Project success is the ultimate goal of the various project stackeholders (Salhi.R 2018). Asuccessful project means that the project is completed on time, within the agreed budget and according to the contract specifications. Delay is one of the most reccuring problems in construction project in Algeria, and it is considered as the main cause of cost overrun, time overrun, disput and claims.The objective of this paper is to mesure the impact of schedule delay on cost overrun, using the simple linear regression method and the coefficient of correlation. The proposed model can be used by practitioners as predictive mesure to address possible cost overrun.

scholarly journals Social capital and the shadow economy: a Bayesian analysis of the BRICS

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tien Ha My Duong ◽  
Thi Anh Nhu Nguyen ◽  
Van Diep Nguyen
Keyword(s):  
Social Capital ◽  
Linear Regression ◽  
Shadow Economy ◽  
Regression Method ◽  
Linear Regression Method ◽  
Content Type ◽  
Brics Countries ◽  
Bayesian Linear Regression ◽  
The Impact ◽  
The Relationship

PurposeThe paper aims to examine the impact of social capital on the size of the shadow economy in the BIRCS countries over the period 1995–2014.Design/methodology/approachThe authors employ the Bayesian linear regression method to uncover the relationship between social capital and the shadow economy. The method applies a normal distribution for the prior probability distribution while the posterior distribution is determined using the Markov chain Monte Carlo technique.FindingsThe results indicate that the unemployment rate and tax burden positively affect the size of the shadow economy. By contrast, corruption control and trade openness are negatively associated with the development of this informal sector. Moreover, the paper's primary finding is that social capital represented by social trust and tax morale can hinder the size of the shadow economy.Research limitations/implicationsThis study is limited to the case of the BRICS countries for the period 1995–2014. The determinants of the shadow economy in different groups of countries can be heterogeneous. Moreover, social capital is a multidimensional concept that may consist of various components. This difficulty of measuring the social capital calls for further research on the relationship between other dimensions of social capital and the shadow economy.Originality/valueMany studies investigate the effect of economic factors on the size of the shadow economy. This paper applies a new approach to discover the issue. Notably, the authors use the Bayesian linear regression method to analyze the relationship between social capital and the shadow economy in the BRICS countries.

scholarly journals Responses of Streamflow to Climate Change and Human Activities in a River Basin, Northeast China

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Hanwen Zhang ◽  
Wei Xu ◽  
Xintong Xu ◽  
Baohong Lu
Keyword(s):  
Water Resources ◽  
Linear Regression ◽  
River Basin ◽  
Human Activities ◽  
Annual Runoff ◽  
Regression Method ◽  
Linear Regression Method ◽  
Climate Elasticity ◽  
The Impact

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources.

scholarly journals The Impact of Family Benefits on Poverty Level in Poland and in Selected European Union Countries

2021 ◽  
pp. 1-7
Author(s):  
Agnieszka Lew ◽  
◽  
Aldona Migała-Warchol ◽  
Monika Pasternak-Malicka ◽  
◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Poverty Level ◽  
Verification Method ◽  
Eu Member States ◽  
Central Statistical ◽  
Family Benefits ◽  
Aid Programs ◽  
The Impact

The purpose: The aim of the article is an attempt to assess the impact of family allowances on the level of poverty among children in selected EU countries. In the paper the division of EU member states by the date of accession to the Community was applied. Methodology: The implementation of the purpose required the use of descriptive and statistical methods, in particular the linear regression method. The ANOVA hypothesis verification method and the Wilcoxon pair order test were also applied using the numerical values of the variables published by the Central Statistical Office for 2015-2016. Results: In the article the essence of the 500+ Program against the background of family benefits in the EU, the level of poverty in Poland and selected countries were described. On the basis of Statistical data downloaded from Eurostat databases for 2016, an attempt was made to assess the impact of the amount of aid programs on the poverty level among h children based on the linear regression method

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

2018 ◽  
Vol 6 (6) ◽  
pp. 119
Author(s):  
Mohammad Shohidul Islam ◽  
Sultana Easmin Siddika ◽  
S M Injamamul Haque Masum
Keyword(s):  
Linear Regression ◽  
Correlation Coefficients ◽  
Rain Gauge ◽  
Regression Method ◽  
Linear Regression Method ◽  
Climate Data ◽  
Rainfall Forecasting ◽  
Statistical Parameters ◽  
Time Duration ◽  
Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

An alternative model of the vibronic coupling in octahedral complexes

1988 ◽  
Vol 53 (6) ◽  
pp. 1134-1140
Author(s):  
Martin Breza ◽  
Peter Pelikán
Keyword(s):  
Linear Regression ◽  
Alternative Model ◽  
Potential Surface ◽  
Analytical Formula ◽  
Coupling Model ◽  
Regression Method ◽  
Vibronic Coupling ◽  
Linear Regression Method ◽  
Active Systems ◽  
Jahn Teller

It is suggested that for some transition metal hexahalo complexes, the Eg-(a1g + eg) vibronic coupling model is better suited than the classical T2g-(a1g + eg) model. For the former, alternative model, the potential constants in the analytical formula are evaluated from the numerical map of the adiabatic potential surface by using the linear regression method. The numerical values for 29 hexahalo complexes of the 1st row transition metals are obtained by the CNDO/2 method. Some interesting trends of parameters of such Jahn-Teller-active systems are disclosed.

Sign in / Sign up

Export Citation Format

Share Document