A Note on Pure Error and Its Effect on Regression Model Significance

2020 ◽  
Vol 35 (1) ◽  
pp. 39-42
Author(s):  
Justin R. Chimka ◽  
Salma Boudhoum ◽  
Katelyn Burrows

AbstractWe extend the concept of maximum coefficient of determination \operatorname{Max}R^{2} caused by repeat runs to ideas about a maximum test statistic F_{0} and a minimum p-value Min P for regression

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1330
Author(s):  
Almalik Mohd Saupi ◽  
Nashiren Mailah ◽  
Mohd Mohd Radzi ◽  
Kamarul Mohamad ◽  
Saiful Ahmad ◽  
...  

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak, with 88.4% of its population located in rural areas and mostly situated along the main riverbanks, has great potential to generate electrical energy with a hydrokinetic system. Yearly water velocity data is the most significant parameter with which to perform a hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilized to estimate the water velocity data. Till present, there is still no publication has been found on estimating of water velocity data in unregulated river using water level. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R2 = 87.4% and R2 = 87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.


2020 ◽  
Vol 1 (2) ◽  
pp. 26-37
Author(s):  
Felicia Eze ◽  
Murat Akyüz ◽  
Opusunju Michael Isaac

Purpose: This study investigates the effect of strategic intent on the performance of small and medium scale printing firms in Federal Capital Territory (FCT), Abuja, Nigeria. Methods: The population of the study included all the small and medium scale printing press in Abuja which is 226 and the sample size of 68. A multiple regression model was formulated to estimate the effect of strategic intent (vision, mission, and objectives) on performance (growth) of small and medium scale printing press firms in Abuja. The study also adopted a control variable such as finance to have a better coefficient of determination. Findings: The study found that strategic intent had a positive and significant effect on the growth of small and medium scale printing press firms in Nigeria. The study also found that finance (collateral, access to finance, and insufficient finance) had a negative and insignificant effect on the growth of small and medium scale printing press firms in Nigeria.  Implication: Small and medium printing press firms in Abuja, FCT should communicate their vision, mission statement, and objectives to their employees. The microfinance banks in collaboration with the central bank of Nigeria should minimize collateral conditions in obtaining microcredit from microfinance banks.   


2015 ◽  
Vol 785 ◽  
pp. 676-681 ◽  
Author(s):  
Nor Shahida Razali ◽  
Nofri Yenita Dahlan

This paper presents the concept of International Performance Measurement and Verification Protocol (IPMVP) for determining energy saving at whole facility level for an office building in Malaysia. Regression analysis is used to develop baseline model from a set of baseline data which correlates baseline energy with appropriate independents variables, i.e. Cooling Degree Days (CDD) and Number of Working Days (NWD) in this paper. In determining energy savings, the baseline energy is adjusted to the same set condition of reporting period using energy cost avoidance approach. Two types of energy saving analyses have been presented in the case study; 1) Single linear regression for each independent variable, 2) Multiple linear regression for each independent variable. Results show that NWD has coefficient of determination, R2 higher than CDD which indicates that NWD has stronger correlation with the energy use than CDD in the building. Finding also shows that the R2 for multiple linear regression model are higher than single linear regression model. This shows the fact that more than one component are affecting the energy use in the building.


Author(s):  
Arvind Keprate ◽  
R. M. Chandima Ratnayake ◽  
Shankar Sankararaman

The main aim of this paper is to perform the validation of the adaptive Gaussian process regression model (AGPRM) developed by the authors for the Stress Intensity Factor (SIF) prediction of a crack propagating in topside piping. For validation purposes, the values of SIF obtained from experiments available in the literature are used. Sixty-six data points (consisting of L, a, c and SIF values obtained by experiments) are used to train the AGPRM, while four independent data sets are used for validation purposes. The experimental validation of the AGPRM also consists of the comparison of the prediction accuracy of AGPRM and Finite Element Method (FEM) relative to the experimentally derived SIF values. Four metrics, namely, Root Mean Square Error (RMSE), Average Absolute Error (AAE), Maximum Absolute Error (MAE), and Coefficient of Determination (R2), are used to compare the accuracy. A case study illustrating the development and experimental validation of the AGPRM is presented. Results indicate that the prediction accuracy of the AGPRM is comparable with and even higher than that of the FEM, provided the training points of the AGPRM are aptly chosen.


1973 ◽  
Vol 53 (3) ◽  
pp. 595-599
Author(s):  
V. D. SHARMA ◽  
L. G. YOUNG

Estimates ranging from 0.30 to 1.00 were evaluated as the value of exponent b of metabolic body size (Wbkg) for young growing pigs by use of a multilinear regression equation HP = q + (1−a) ME + ak Wbkg. Data on heat production, metabolizable energy intake, and average empty body weight for 87 pigs, ranging from 5 to 35 kg liveweight, of Lacombe, Yorkshire, Hampshire × Yorkshire, and Lacombe × Yorkshire breeding and for all pigs combined were used in this study. The criteria of best fit were the maximum coefficient of determination and the minimum coefficient of variation. The use of a particular exponent from 0.30 to 1.00 did not markedly influence the best fit. Differences in R2 and C.V. from using different exponent values were negligible. Because the results of this study and those from the literature suggest that no marked variation in precision results from using different values of exponent b, the use of 0.75 as the general reference base in calculating metabolic body size for growing pigs is recommended.


2016 ◽  
Vol 12 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Kianoosh Pirnazari ◽  
Ali Esehaghbeygi ◽  
Morteza Sadeghi

Abstract Electrohydrodynamic (EHD) drying of banana slices was modeled both numerically and empirically. The drying process was conducted using the EHD technique at 6, 8, and 10 kV cm−1 with banana slices 3 mm thick. Based on the maximum coefficient of determination (R2) and minimum value of root mean square of error (RMSE) observed in the experimental and predicted values of moisture ratio, the diffusion model was identified as the best prediction model. The values for effective moisture diffusivity were calculated to be in the range of 3.12 × 10−10 to 4.23 × 10−10 m2 s−1. In addition, a theoretical model was developed using the numerical (implicit) solution of the second Fick’s equation based on low variation in the external resistance by applying EHD. Moisture ratio versus time showed a falling rate period indicating that the internal moisture transfer is dominant at EHD. Results of numerical solution showed adequate consistency with experimental data, having the maximum difference of less than 0.16 g g−1 in moisture content.


2011 ◽  
Vol 8 (9) ◽  
pp. 2567-2579 ◽  
Author(s):  
S. J. McCoy ◽  
L. F. Robinson ◽  
C. A. Pfister ◽  
J. T. Wootton ◽  
N. Shimizu

Abstract. A distinct gap in our ability to understand changes in coastal biology that may be associated with recent ocean acidification is the paucity of directly measured ocean environmental parameters at coastal sites in recent decades. Thus, many researchers have turned to sclerochronological reconstructions of water chemistry to document the historical seawater environment. In this study, we explore the relationships between B/Ca and pH to test the feasibility of B/Ca measured on the ion probe as a pH proxy in the California mussel, Mytilus californianus. Heterogeneity in a range of ion microprobe standards is assessed, leading to reproducible B/Ca ratios at the 5% level. The B/Ca data exhibit large excursions during winter months, which are particularly pronounced during the severe winters of 2004–2005 and 2005–2006. Furthermore, B/Ca ratios are offset in different parts of the skeleton that calcified at the same time. We compare the M. californianus B/Ca record to directly measured environmental data during mussel growth from the period of 1999–2009 to examine whether seawater chemistry or temperature plays a role in controlling shell B/Ca. A suite of growth rate models based on measured temperature are compared to the B/Ca data to optimise the potential fit of B/Ca to pH. Despite sampling conditions that were well-suited to testing a pH control on B/Ca, including a close proximity to an environmental record, a distinct change in pH at the sampling locale, and a growth model designed to optimise the correlations between seawater pH and shell B/Ca, we do not see a strong correlations between pH and shell B/Ca (maximum coefficient of determination, r2, of 0.207). Instead, our data indicate a strong biological control on B/Ca as observed in some other carbonate-forming organisms.


Author(s):  
Malika Nefti Budi Asih ◽  
Hutomo Atman Maulana

This study aims to determine the effect of Service Quality, Price, and Brand Loyalty on Motorcycle Purchase Decisions at dealer CV.Andalas Motor Bengkalis. This research is associative research. The population used by consumers who buy motorbikes at dealer CV Andalas Motor Bengkalis with a sample size of 100 respondents. The technique used is multiple linear regression with the regression model Y=1.821 + 0.163X1 + 0.299X2 + 0.207X3 + e. The results of this study indicate that partially service quality has a positive and significant effect on purchasing decisions with tcount 2.466, price has a positive and significant effect on purchasing decisions with tcount 4.045. Brand loyalty has a positive and significant effect on purchasing decisions with tcount 6.158. Simultaneously, Service Quality, Price, and Brand Loyalty have a positive and significant effect on motorcycle purchasing decisions at dealer CV.Andalas Motor Bengkalis with Fcount 67.837 seen from the coefficient of determination 67.9%.


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