Development of a Multiple Linear Regression Model for Meteorological Drought Index Estimation Based on Landsat Satellite Imagery

Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remote sensing and climate data for Boryeong, Chungcheongnam-do, Korea, and developed a model for drought index estimation by classifying data characteristics and applying multiple linear regression analysis. The drought indices estimated in this study include four types of standardized precipitation indices (SPI1, SPI3, SPI6, and SPI9) used as meteorological drought indices and calculated through cumulative precipitation. We then applied statistical analysis to the developed model and assessed its ability as a drought index estimation tool using remote sensing data. Our results showed that its adj.R2 value, achieved using cumulative precipitation for one month, was very low (approximately 0.003), while for the SPI3, SPI6, and SPI9 models, the adj.R2 values were significantly higher than the other models at 0.67, 0.64, and 0.56, respectively, when the same data were used.

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Predictive Factors for Hamstring Autograft Diameter in Anterior Cruciate Ligament Reconstruction

The Journal of Knee Surgery ◽

10.1055/s-0039-1700495 ◽

2019 ◽

Author(s):

Willem M.P. Heijboer ◽

Mathijs A.M. Suijkerbuijk ◽

Belle L. van Meer ◽

Eric W.P. Bakker ◽

Duncan E. Meuffels

Keyword(s):

Anterior Cruciate Ligament ◽

Linear Regression ◽

Multiple Linear Regression ◽

Acl Reconstruction ◽

Cruciate Ligament ◽

Linear Regression Analysis ◽

Multiple Linear Regression Model ◽

Gracilis Tendon ◽

Thigh Circumference ◽

Anterior Cruciate

AbstractMultiple studies found hamstring tendon (HT) autograft diameter to be a risk factor for anterior cruciate ligament (ACL) reconstruction failure. This study aimed to determine which preoperative measurements are associated with HT autograft diameter in ACL reconstruction by directly comparing patient characteristics and cross-sectional area (CSA) measurement of the semitendinosus and gracilis tendon on magnetic resonance imaging (MRI). Fifty-three patients with a primary ACL reconstruction with a four-stranded HT autograft were included in this study. Preoperatively we recorded length, weight, thigh circumference, gender, age, preinjury Tegner activity score, and CSA of the semitendinosus and gracilis tendon on MRI. Total CSA on MRI, weight, height, gender, and thigh circumference were all significantly correlated with HT autograft diameter (p < 0.05). A multiple linear regression model with CSA measurement of the HTs on MRI, weight, and height showed the most explained variance of HT autograft diameter (adjusted R 2 = 44%). A regression equation was derived for an estimation of the expected intraoperative HT autograft diameter: 1.2508 + 0.0400 × total CSA (mm2) + 0.0100 × weight (kg) + 0.0296 × length (cm). The Bland and Altman analysis indicated a 95% limit of agreement of ± 1.14 mm and an error correlation of r = 0.47. Smaller CSA of the semitendinosus and gracilis tendon on MRI, shorter stature, lower weight, smaller thigh circumference, and female gender are associated with a smaller four-stranded HT autograft diameter in ACL reconstruction. Multiple linear regression analysis indicated that the combination of MRI CSA measurement, weight, and height is the strongest predictor.

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Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

Journal of Climate ◽

10.1175/2010jcli3812.1 ◽

2011 ◽

Vol 24 (8) ◽

pp. 2025-2044 ◽

Cited By ~ 249

Author(s):

Martha C. Anderson ◽

Christopher Hain ◽

Brian Wardlow ◽

Agustin Pimstein ◽

John R. Mecikalski ◽

...

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Drought Index ◽

Temporal Correlation ◽

Meteorological Drought ◽

Rainfall Data ◽

Added Value ◽

Stress Index ◽

Drought Indices ◽

Shallow Water Table

Abstract The reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–09 growing seasons. Spatial and temporal correlation analyses suggest that the ESI performs similarly to short-term (up to 6 months) precipitation-based indices but can be produced at higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall: for example, in areas of intense irrigation or shallow water table. Normalization by PET serves to isolate the ET signal component responding to soil moisture variability from variations due to the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.

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Effects of Total Quality Management (TQM) Dimensions on Innovation—Evidence from SMEs

Sustainability ◽

10.3390/su131810095 ◽

2021 ◽

Vol 13 (18) ◽

pp. 10095

Author(s):

Marina Godinho Antunes ◽

Pedro Ribeiro Mucharreira ◽

Maria Rosário Texeira Justino ◽

Joaquín Texeira-Quirós

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Continuous Improvement ◽

Product Innovation ◽

Research Study ◽

Linear Regression Analysis ◽

Multiple Linear Regression Model ◽

Process Innovation ◽

Total Quality ◽

Innovation Strategies

This research study aims to study and identify which dimensions of TQM have influence on and support innovation strategies within the Portuguese small and medium enterprises (SMEs), in the context of products or services’ innovation and process innovation, as well as to analyze the extent to which this relationship occurs. To examine the linkage between TQM dimensions and innovation strategies, concerning innovation products and innovation processes, a multiple linear regression analysis was chosen and an eight-predictor multiple linear regression model was proposed. The data was collected through a questionnaire sent by email. This research study allows to conclude that several dimensions of TQM, such as benchmarking, quality/conception and product design, and continuous improvement, have a significant and positive association with product innovation. Although the data analysis/measurement of the results dimension has a significant association with product innovation, this association is negative. Conversely, several TQM dimensions, such as leadership/management’s commitment, benchmarking, involvement/empowerment of employees, and continuous improvement, revealed a positive and significant association with process innovation. Our research is of crucial importance for the knowledge of Portuguese SMEs and the fundamental factors that companies must address to both improve their efficiency and be more competitive, thereby increasing profitability and ensuring financial sustainability in the medium and long term.

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ANALISIS PENGARUH LIKUIDITAS, STRUKTUR AKTIVA, FREE CASH FLOW, DAN UKURAN PERUSAHAAN TERHADAP KEBIJAKAN UTANG (DER) PADA PT JASA MARGA Tbk PERIODE 2009-2018

KEUNIS ◽

10.32497/keunis.v7i2.1588 ◽

2019 ◽

Vol 7 (2) ◽

pp. 92

Author(s):

Anita Kristina ◽

Prihatiningsih Prihatiningsih ◽

Ida Savitri Kusmargiani

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Cash Flow ◽

Linear Regression Analysis ◽

Multiple Linear Regression Model ◽

Multiple Linear Regression Analysis ◽

Free Cash Flow ◽

Company Size ◽

Analysis Model ◽

Debt Policy

<em>This research is based on the problems of the company PT Jasa Marga Tbk which has a problem with the performance of the company which is indicated by the DER of companie increased during the period 2009-2018. The purpose of this research is to analyze the influance of direction and significance of Liquidity, Asset Structure, Free Cash Flow and Company Size on Debt Policy (DER) in PT Jasa Marga Tbk for the period 2009-2018. The population and sample in this study were PT Jasa Marga Tbk. The analysis model used in this study is a multiple linear regression model. The results of the multiple linear regression analysis showed that (1) the influance of Liquidity (CR) on Debt Policy (DER) was positive and significant (2) the influance Asset Structure on Debt Policy (DER) was negative and not significant (3) the influance of Free Cash Flow on Debt Policy (DER) is positive and significant (4) the influance of Company Size on Debt Policy (DER) is positive and significant.</em>

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A Mathematical Comparison of the Lachance - Traill Matrix Correction Procedure with Statistical Multiple Linear Regression Analysis in XRF Applications

Advances in X-ray Analysis ◽

10.1154/s0376030800018577 ◽

1992 ◽

Vol 36 ◽

pp. 1-10

Author(s):

Anthony J. Klimasara

Keyword(s):

Linear Regression ◽

Regression Model ◽

Multiple Linear Regression ◽

Linear Regression Model ◽

Linear Regression Analysis ◽

Multiple Linear Regression Model ◽

Mathematical Meaning ◽

Matrix Correction ◽

Independent Variables ◽

Xrf Analysis

AbstractIt will be shown that the Lachance-Traill XRF matrix correction equations can be derived from the statistical multiple linear regression model. By selecting and properly transforming the independent variables and then applying the statistical multiple linear regression model, the following form of the matrix correction equation is obtained:Furthermore, it will be shown that the Lachance-Traill influence coefficients have a deeper mathematical meaning. They can be related to the multiple regression coefficients of the transformed system:Finally, it will be proposed that the Lachance-Traill model is equivalent to the statistical multiple linear regression model with the transformed independent variables. Knowing these facts will simplify correction subroutines in Quantitative/Empirical XRF Analysis programs. These mathematical facts have already been implemented and presented in a paper: “Automated Quantitative XRF Analysis Software in Quality Control Applications” (Pacific-International Congress on X-ray Analytical Methods, Hawaii, 1991).This demonstrates that the Lachance-Traill model has a strong mathematical foundation and is naturally justified mathematically.

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A linear regression pattern for electricity price forecasting in the Iberian electricity market

Revista Facultad de Ingeniería Universidad de Antioquia ◽

10.17533/udea.redin.20190522 ◽

2019 ◽

pp. 117-127

Author(s):

Ângela Paula Ferreira ◽

Jenice Gonçalves Ramos ◽

Paula Odete Fernandes

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Linear Regression Analysis ◽

Multiple Linear Regression Model ◽

Electricity Price ◽

Price Forecasting ◽

Electricity Prices ◽

Market Participants ◽

Electricity Price Forecasting ◽

The Impact

The Iberian Market for Electricity resulted from a cooperation process developed by the Portuguese and Spanish administrations, aiming to promote the integration of the electrical systems of both countries. This common market consists of organized markets or power exchanges, and non-organised markets where bilateral over-the-counter trading takes place with or without brokers. Within this scenario, electricity price forecasts have become fundamental to the process of decision-making and strategy development by market participants. The unique characteristics of electricity prices such as non-stationarity, non-linearity and high volatility make this task very difficult. For this reason, instead of a simple time forecast, market participants are more interested in a causal forecast that is essential to estimate the uncertainty involved in the price. This work focuses on modelling the impact of various explanatory variables on the electricity price through a multiple linear regression analysis. The quality of the estimated models obtained validates the use of statistical or causal methods, such as the Multiple Linear Regression Model, as a plausible strategy to achieve causal forecasts of electricity prices in medium and long-term electricity price forecasting. From the evaluation of the electricity price forecasting for Portugal and Spain, in the year of 2017, the mean absolute percentage errors (MAPE) were 9.02% and 12.02%, respectively. In 2018, the MAPE, evaluated for 9 months, for Portugal and Spain equals 7.12% and 6.45%, respectively.

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Quantification of Concrete Waste Generated in Housing Construction Sites via Site Sampling: Development of a Multiple Linear Regression Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.802.676 ◽

2015 ◽

Vol 802 ◽

pp. 676-681

Author(s):

Siti Hafizan Hassan ◽

Hamidi Abdul Aziz ◽

Izwan Johari ◽

Mohd Nordin Adlan

Keyword(s):

Linear Regression ◽

Regression Model ◽

Multiple Linear Regression ◽

Linear Regression Analysis ◽

Estimation Method ◽

Multiple Linear Regression Model ◽

Real Data ◽

Housing Construction ◽

Construction Sites ◽

Average Percentage

Waste generated in construction sites has recently increased and has become an uncontrollable cause of environmental problems and profit loss to contractors. The lack of real data or research on such wastes is due to the lack of suitable policies regarding this issue. The actions of contractors are not controlled by rules on this issue. This situation leads to the lack of action or awareness on the side of the contractor. Concrete waste is also part of the waste generated in construction sites. We determine the concrete waste generated in construction stages and conduct multiple linear regression analysis of the amount of column waste generated. The methodology employed in this study involves site observations, interviews with site personnel, and sampling at housing construction sites. The estimation method is utilized for the sampling of concrete waste. Results show that the average percentage of column waste is 13.93% and that of slab waste is 0.34%. These percentage values are derived from the total order of the concrete. The difference is due to the sizes of structures and method of handling. The regression model obtained from the sample data on column waste resulted in an adjustedR2value of 0.895. Therefore, the model predicts approximately 89.5% of the factors involved in concrete waste generation.

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Pertumbuhan Arus Kas, Pertumbuhan Laba, Inflasi, Suku Bunga, Nilai Kurs dan Return Saham pada Badan Usaha Milik Negara di Bursa Efek Indonesia

Jurnal Riset Akuntansi & Perpajakan (JRAP) ◽

10.35838/jrap.v1i02.76 ◽

2014 ◽

Vol 1 (02) ◽

pp. 171-186

Author(s):

Moh. Abror ◽

Dadang Sadeli

Keyword(s):

Linear Regression ◽

Exchange Rates ◽

Interest Rates ◽

Multiple Linear Regression ◽

Stock Returns ◽

Sampling Method ◽

Linear Regression Analysis ◽

Multiple Linear Regression Model ◽

Earning Growth ◽

Purposive Sampling

ABSTRACT The study aims to analyze the effect of cashflow growth, earning growth, inflation, interest rates and exchange rates to stock return BUMN. The sample selection is done by using purposive sampling method. Acquired a total sample of 15 companies of 19 state-owned companies listed in Indonesia Stock Exchange during the period 2009 - 2012. This study used multiple linear regression analysis techniques to examine the effect of the independent variable on the dependent variable. Based on the results of the study, there were no variables that deviated of the classical assumption, it indicates that the available data are qualified to use a multiple linear regression model. The results showed that the growth in cash flow, earnings growth, interest rates and exchange rates had no significant effect on stock returns. The study able to show that the interest rate significant positive effect on stock returns. ABSTRAK Penelitian bertujuan untuk menganalisis pengaruh pertumbuhan arus kas, pertumbuhan laba, inflasi, suku bunga dan nilai kurs terhadap return saham BUMN. Pemilihan sampel dilakukan dengan menggunakan purposive sampling method. Diperoleh jumlah sampel sebanyak 15 perusahaan dari 19 perusahaan BUMN yang terdaftar di Bursa Efek Indonesia selama periode 2009 – 2012. Penelitian ini menggunakan teknik analisa regresi linear berganda untuk menguji pengaruh variable independen terhadap variable dependen. Berdasarkan hasil penelitian, tidak ditemukan variabel yang menyimpang dari asumsi klasik, hal ini menunjukkan bahwa data yang tersedia telah memenuhi syarat untuk menggunakan model persamaan regresi linier berganda. Hasil penelitian menunjukkan bahwa pertumbuhan arus kas, pertumbuhan laba, suku bunga dan nilai kurs tidak berpengaruh signifikan terhadap return saham. Penelitian berhasil membuktikan bahwa suku bunga berpengaruh positif signifikan terhadap return saham BUMN. JEL Classification: G14, G30

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Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

Journal of Hydroinformatics ◽

10.2166/hydro.2021.025 ◽

2021 ◽

Author(s):

Christopher Papadopoulos ◽

Mike Spiliotis ◽

Ioannis Gkiougkis ◽

Fotios Pliakas ◽

Basil Papadopoulos

Keyword(s):

Linear Regression ◽

Linear Regression Analysis ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Drought Indices ◽

Fuzzy Linear Regression ◽

Aquifer System ◽

Irrational Behavior ◽

Groundwater Response ◽

Linear Regressions

Abstract This paper studies, through the principles of fuzzy set theory, groundwater response to meteorological drought in the case of an aquifer system located in the plains at the southeast of Xanthi, NE Greece. Meteorological drought is expressed through standardized Reconnaissance Drought Index (RDISt) and Standardized Precipitation Index (SPI), which are calculated for various reference periods. These drought indices are considered as independent variables in multiple fuzzy linear regression based on Tanaka's model, while the observed water table regarding two areas is used as a dependent variable. The fuzzy linear regression of Tanaka is characterized by the inclusion constraints where all the observed data must be included in the produced fuzzy band. Hence, each fuzzy output can get an interval of values where a membership degree corresponds to each of them. A modification of the Tanaka model by adding constraints is proposed in order to avoid irrational behavior. The results show that there was a significant influence of the meteorological drought of the previous hydrological year, while geology plays an important role. Furthermore, the use of RDISt improves the results of fuzzy linear regressions in all cases. Two suitability measures and a measure of comparison between fuzzy numbers are used.

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Association between the Type of Workplace and Lung Function in Copper Miners

BioMed Research International ◽

10.1155/2016/5928572 ◽

2016 ◽

Vol 2016 ◽

pp. 1-15 ◽

Cited By ~ 8

Author(s):

Anna Skoczyńska ◽

Leszek Gruszczyński ◽

Anna Wojakowska ◽

Marek Ścieszka ◽

Barbara Turczyn ◽

...

Keyword(s):

Lung Function ◽

Linear Regression ◽

Multiple Linear Regression ◽

Linear Regression Analysis ◽

Longitudinal Data Analysis ◽

Multiple Linear Regression Model ◽

Multiple Linear Regression Analysis ◽

Analysis Software ◽

Cross Sectional ◽

Sectional Analysis

The aim of the analysis was to retrospectively assess changes in lung function in copper miners depending on the type of workplace. In the groups of 225 operators, 188 welders, and 475 representatives of other jobs, spirometry was performed at the start of employment and subsequently after 10, 20, and 25 years of work. Spirometry Longitudinal Data Analysis software was used to estimate changes in group means for FEV1and FVC. Multiple linear regression analysis was used to assess an association between workplace and lung function. Lung function assessed on the basis of calculation of longitudinal FEV1 (FVC) decline was similar in all studied groups. However, multiple linear regression model used in cross-sectional analysis revealed an association between workplace and lung function. In the group of welders, FEF75 was lower in comparison to operators and other miners as early as after 10 years of work. Simultaneously, in smoking welders, the FEV1/FVC ratio was lower than in nonsmokers (p< 0,05). The interactions between type of workplace and smoking (p< 0,05) in their effect on FVC, FEV1, PEF, and FEF50 were shown. Among underground working copper miners, the group of smoking welders is especially threatened by impairment of lung ventilatory function.

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