scholarly journals Multiple Regression Equations for Estimating Water Supply Capacities of Dams Considering Influencing Factors

2012 ◽  
Vol 45 (11) ◽  
pp. 1131-1141 ◽  
Author(s):  
Min Goo Kang ◽  
Gwang Man Lee
Keyword(s):  
Water Supply ◽  
Multiple Regression ◽  
Influencing Factors ◽  
Regression Equations

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

Estimation de la production de jeunes plantations de pin rouge et de pin gris du sud du Québec

1976 ◽  
Vol 6 (4) ◽  
pp. 478-486 ◽  
Author(s):  
H. A. Bolghari
Keyword(s):  
Multiple Regression ◽  
Jack Pine ◽  
Red Pine ◽  
Pine Plantations ◽  
Regression Equations ◽  
Pine Plantation ◽  
South Shore ◽  
Pine Stands ◽  
Natural Stands ◽  
St Lawrence River

Multiple regression equations have been developed to predict yield from young red pine and jack pine plantations. Data from 446 sample plots representing young red pine and jack pine stands located on the south shore of the St. Lawrence River between Quebec and Montreal were analysed. The red pine plantation yielded more than the jack pine. However, in plantation both species yield more than in natural stands. Taking into account the age and spacing of the sampled plantations, the equation obtained can provide information on yield of red pine and jack pine stands the maximum spacing of which is 3 × 3 m, up to the age of 45 and 35 years respectively. The equations will allow the construction of preliminary yield tables for both species.

FAT THICKNESS MEASURED WITH THREE ULTRASONIC INSTRUMENTS ON LIVE RAM LAMBS AS PREDICTORS OF CUTABILITY

1980 ◽  
Vol 60 (4) ◽  
pp. 857-867 ◽  
Author(s):  
ANDRÉ FORTIN
Keyword(s):  
Multiple Regression ◽  
Live Weight ◽  
Optimal Location ◽  
Regression Equations ◽  
Longissimus Muscle ◽  
Fat Thickness ◽  
Ram Lambs

Fat thickness at four locations over the longissimus muscle was measured ultrasonically on 33 live ram lambs ranging in live weight from 16.0 to 37.0 kg. Simple and multiple regression equations were developed to assess the effectiveness of fat thickness as measured by three different ultrasonic instruments (Krautkrämer USM #2, Scanoprobe Model 731A and Scanogram Model 722) to predict cutability. Weight of trimmed or boneless cuts (shoulder + loin + rack + leg) was predicted with more precision than percentage of cuts. Fat thickness alone or combined with weight at scanning was of no significant value (P > 0.05) in the prediction of percentage of trimmed cuts. Percentage of boneless cuts was predicted more efficiently from weight at scanning alone than from fat thickness alone or combined with weight at scanning. Weight of cuts (trimmed or boneless) was also estimated from the fat measurement (P < 0.01), the weight at scanning (P < 0.01) or a combination of both variables. For the latter, fat thickness did not contribute significantly (P > 0.05). The optimal location of the fat measurement depended on the ultrasonic instrument used. Fat thickness measured with the Krautkrämer was more efficient in its prediction of cutability than fat thickness measured with the Scanoprobe or Scanogram. However, over the range of liveweights studied, the usefulness of fat thickness measured on live ram lambs to predict cutability is questionable.

scholarly journals Pengaruh Karakteristik, Sikap, Dan Keterampilan Wirausahawan Rumah Makan Pempek Di Kota Palembang Terhadap Keberhasilan Usaha

2019 ◽  
Vol 17 (1) ◽  
pp. 92
Author(s):  
Andreas Sarjono ◽  
Maria Josephine Tyra
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Influencing Factors ◽  
Sampling Technique ◽  
T Test ◽  
Purposive Sampling ◽  
Successful Business

A study entitled �The Influence of Characteristics, Attitude and Skill of Pempek Entrepreneurs in Palembang toward Successful Business Achievement� is an entrepreneurship study related to the influencing factors of succesful business achievement of pempek entrepreneurs in Palembang. This purpose of this study is to find out whether or not the entrepreneurs� characteristics, attitude and skill factors affect the succesful business achievement. Sample was selected by using purposive sampling technique. The hypothesis was tested by using multiple regression analysis. The t-test of SPSS calculation implied that the significant value of characteristics was 0.709, attitude was 0.213 and entrepreneurship skill was 0.287 (less than 0.05). Therefore, the results of the study implied that there was no correlation between characteristics, attitude and entrepreneurship skill of pempek entrepreneurs in Palembang toward succesful business achievement.

EQUATIONS FOR RECIPROCAL CONVERSIONS OF STARCH EQUIVALENT AND TOTAL DIGESTIBLE NUTRIENT VALUES

1962 ◽  
Vol 42 (2) ◽  
pp. 211-214
Author(s):  
J. Kielanowski ◽  
Aleksandra Ziolecka ◽  
Zofia Osińska
Keyword(s):  
Multiple Regression ◽  
Fiber Content ◽  
Crude Fiber ◽  
Regression Equations ◽  
Crude Fiber Content ◽  
Independent Variable ◽  
Total Digestible Nutrient

In order to facilitate reciprocal conversions of Starch Equivalents (SE) and Total Digestible Nutrients (TDN) values of feeds, multiple regression equations were computed for three different groups of feeds (concentrates, green roughages and silages, and dry roughages. These equations are: for concentrates, green roughages and silages, and dry roughages, respectively.[Formula: see text]Where Y = percentage TDN, X1 = percentage SE, and X2 = percentage crude fiber and[Formula: see text]Where Y = percentage SE; X1 = percentage TDN, and X2 = percentage crude fiber.The addition of the crude fiber content as the second independent variable in each equation resulted in a slight but marked gain in accuracy, especially for green and dry roughages, when compared with simple regressions of TDN on SE or vice versa.

scholarly journals Generalized equations for predicting body density of men

1978 ◽  
Vol 40 (3) ◽  
pp. 497-504 ◽  
Author(s):  
A. S. Jackson ◽  
M. L. Pollock
Keyword(s):  
Multiple Regression ◽  
Skinfold Thickness ◽  
Standard Errors ◽  
Regression Equations ◽  
Generalized Equations ◽  
Body Density ◽  
Adult Men ◽  
Body Circumferences

1. Skinfold thickness, body circumferences and body density were measured in samples of 308 and ninety-five adult men ranging in age from 18 to 61 years.2. Using the sample of 308 men, multiple regression equations were calculated to estimate body density using either the quadratic or log form of the sum of skinfolds, in combination with age, waist and forearm circumference.3. The multiple correlations for the equations exceeded 0.90 with standard errors of approximately ±0.0073 g/ml.4. The regression equations were cross validated on the second sample of ninety-five men. The correlations between predicted and laboratory-determined body density exceeded 0.90 with standard errors of approximately 0.0077 g/ml.5. The regression equations were shown to be valid for adult men varying in age and fatness.

Accuracy of the Multiple-Regression Method for Estimating Population-Density in Strip Transects

1986 ◽  
Vol 13 (2) ◽  
pp. 121 ◽  
Author(s):  
J Hone
Keyword(s):  
Population Density ◽  
Multiple Regression ◽  
Robust Estimation ◽  
Aerial Survey ◽  
Regression Method ◽  
Regression Equations ◽  
Regression Analyses ◽  
True Density ◽  
Balanced Design ◽  
Multiple Regression Method

Two experiments examined the accuracy of the multiple regression method for estimating population density. In experiment I , in a balanced design, an observer counted objectsin simulated strip transects. Multiple regression analyses yielded accurate estimates when true density was low, and overestimated density when true density was high. Regression equations calculated at each level of true density varied from linear to quadratic. A simple polynomial model accurately estimated true density. In experiment 2 an aerial survey of sheep showed that estimated density was highly significantly (P <0.001) different from true density. The results suggest that greater use should be made of established criteria for robust estimation of true density in transect studies.

The Appetite Potential of Jersey Cows

1984 ◽  
Vol 1984 ◽  
pp. 125-125
Author(s):  
T. D. A. Brigstocke ◽  
M. A. Lindeman
Keyword(s):  
Body Size ◽  
Multiple Regression ◽  
Dry Matter ◽  
Regression Equations ◽  
Previous Trial ◽  
Jersey Cows

A previous trial (Brigstocke et al., 1982) had indicated that mature Jersey cows ate considerably more dry matter (DM) in relation to their body size than was currently projected from the multiple regression equations used for appetite prediction. However this trial was run on one large high-yielding herd with only a small number of animals and it was not known whether the results were applicable to the more average Jersey producer.

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