Output and Policy Ineffectiveness Proposition: A Perspective from Single Regression Equations

2019 ◽  
pp. 367-376
Author(s):  
Eliphas Ndou ◽  
Thabo Mokoena
Keyword(s):  
Regression Equations ◽  
Single Regression

Estimating mass of temperate and tropical pastures in the subtropics

1993 ◽  
Vol 33 (7) ◽  
pp. 865 ◽  
Author(s):  
WJ Fulkerson ◽  
K Slack
Keyword(s):  
Substantial Reduction ◽  
Ground Level ◽  
Regression Equations ◽  
Tropical Pastures ◽  
Senescent Leaf ◽  
Temperate Pastures ◽  
Second Year ◽  
Single Regression ◽  
Separate Regression ◽  
Subtropical Environment

The feasibility of estimating, with acceptable precision, temperate and tropical pasture mass in a subtropical environment was evaluated. For the tropical grasses kikuyu (Pennisetum clandestinum) and setaria (Setaria ancepts), 3 different pasture meters were calibrated against 1 of 3 dry matter (DM) estimates. Temperate pastures (predominantly Lolium perenne and Trifolium repens) were evaluated using the Ellinbank rising plate meter (RPMl) calibrated against DM to ground level. A single regression equation was developed for syegrass-white clover pasture from data pooled within season over first- and second-year swards. The s.e. of estimate (s.e.e.) for assessing tropical grass pasture mass using RPMl was similar to that for a heavier Ellinbank meter and substantially lower than that for the electronic pasture probe. Using RPMl, separate regression equations were required for early (November-February) and late (March-May) season determinations for both kikuyu and setaria. The regression equations were based on calibrations against shoot DM (>5 cm stubble height for kikuyu and 6 cm for setaria) and are only applicable to well-managed and highly utilised pastures. Calibrations of all pasture meters over all months to green DM (senescent leaf and stem removed) gave a lower s.e.e. than total DM (kikuyu 138 v. 177 kg DM/ha, n = 171; setaria 211 v. 224 kg DM/ha, n = 177) whilst shoot DM gave a more substantial reduction in s.e.e. (kikuyu 95 v. 147 kg DM/ha; setaria 140 v. 193 kg DM/ha).

Comparaison des équations de régression. Application au cubage des arbres d'épinette noire.

1979 ◽  
Vol 55 (2) ◽  
pp. 54-56
Author(s):  
Richard Zarnovican
Keyword(s):  
Black Spruce ◽  
Regression Equation ◽  
Regression Equations ◽  
Soil Drainage ◽  
Total Height ◽  
Reduced Height ◽  
Bartlett Test ◽  
Single Regression

The Bartlett test, parallelism test and coincidence test were applied to compare four regression equations. The comparison dealt with regression equations for reduced height from total height of black spruce for four soil drainages, over till, in the High Subarctic of Quebec. It was found that form height can be extracted from total height by means of a single regression equation where soil drainage is good, moderately good or imperfect, but that a separate equation is required where drainage is poor.

Computer Assistance in the Clinical Investigation of Pulmonary Function Studies

1973 ◽  
Vol 12 (02) ◽  
pp. 102-107 ◽  
Author(s):  
D. J. Protti ◽  
Nancy Craven ◽  
A. Naimark ◽  
R. M. Cherniack
Keyword(s):  
Information System ◽  
Pulmonary Function ◽  
Additional Data ◽  
Normal Values ◽  
Clinical Investigation ◽  
Regression Equations ◽  
Beneficial Effects ◽  
Computer Assistance ◽  
Manual Methods

A previously described comprehensive respiratory information system (CRIS) has been changed to introduce new spirometric tests which are sensitive to minor abnormalities, revise on the basis of additional data the regression equations which define normal values to various parameters of pulmonary function and refine the system’s interpretation scheme. The beneficial effects of transferring the system from a large IBM 360/65 to a small CDC 1700 are presented. An analysis of the costs of processing routine pulmonary function studies reveals that a 40°/o saving is realized when a computer is used in comparison to the use of the usual manual methods.

Studying the factors of regional insurance market development using the correlation and regression analysis

2020 ◽  
Vol 26 (7) ◽  
pp. 1610-1630
Author(s):  
E.L. Prokop'eva
Keyword(s):  
Regression Analysis ◽  
Federal District ◽  
Insurance Market ◽  
Market Development ◽  
Insurance Markets ◽  
Regression Equations ◽  
Factors Affecting ◽  
Correlation And Regression Analysis ◽  
Country Level ◽  
Inverse Effect

Subject. The article investigates and quantifies factors of insurance markets functioning in Russian regions, and reveals possibilities to manage them. Objectives. The purpose of the study is to substantiate regional factors that determine the specifics of regional insurance market development; to quantify them to increase the efficiency of regional insurance. Methods. The study draws on statistical methods, functional analysis, algorithm development, correlation and regression analysis. Results. I calculated coefficients of pair and multiple correlation with the indicators of insurance markets in the context of the subjects of the Russian Federation, and composed regression equations. Based on the analysis, I determined the algorithm for inverse effect of the insurance market on the economic, social, fiscal and environmental performance of the region, offered appropriate measures aimed at developing the economic potential of the region and its social sphere. Conclusions. The paper considers the case of the Republic of Khakassia, one of depressed subjects in the Siberian Federal District. The developed models can be used for other regions of Russia, given the geographical and economic features of development. The findings may help generate regional strategies for socio-economic development at the country level. The scientific contribution and the novelty of the work consist of systematizing and quantifying the factors affecting the insurance mechanisms of regional markets, and assessing the inverse effect of insurance mechanisms on integrated development of the region.

Investigation of the effect of the constructive and mode parametres of a combined rocker on the power of the drive of the working bodies

2019 ◽  
pp. 82-85
Author(s):  
Pavel Ivanovich Pavlov ◽  
Viktor Vladislavovich Korsak ◽  
Aleksandr Olegovich Vezirov ◽  
Dmitriy Vadimovich Mukhin
Keyword(s):  
Operating Parameters ◽  
Regression Equations ◽  
Drive Power ◽  
Minimum Value ◽  
Working Bodies

The regression equations and graphical dependencies are obtained, which describe the influence of design and operating parameters on the drive power of the working bodies. The value of the design and operating parameters in which the power required to drive the working bodies, will have a minimum value  are experimentally determined.

County-level USA: No Robust Relationship between Geoclimatic Variables and Cognitive Ability

2020 ◽  
Author(s):  
Bryan J Pesta ◽  
John Fuerst ◽  
Emil O. W. Kirkegaard
Keyword(s):  
Cognitive Ability ◽  
Climate Models ◽  
Cold Weather ◽  
Regression Equations ◽  
County Level ◽  
Spatial Lag ◽  
Average Temperature ◽  
Wrong Direction ◽  
Race Ethnicity ◽  
Demographic Covariates

Using a sample of ~3,100 U.S. counties, we tested geoclimatic explanations for why cognitive ability varies across geography. These models posit that geoclimatic factors will strongly predict cognitive ability across geography, even when a variety of common controls appear in the regression equations. Our results generally do not support UV radiation (UVR) based or other geoclimatic models. Specifically, although UVR alone predicted cognitive ability at the U.S. county-level (β = -.33), its validity was markedly reduced in the presence of climatic and demographic covariates (β = -.16), and was reduced even further with a spatial lag (β = -.10). For climate models, average temperature remained a significant predictor in the regression equation containing a spatial lag (β = .35). However, the effect was in the wrong direction relative to typical cold weather hypotheses. Moreover, when we ran the analyses separately by race/ethnicity, no consistent pattern appeared in the models containing the spatial lag. Analyses of gap sizes across counties were also generally inconsistent with predictions from the UVR model. Instead, results seemed to provide support for compositional models.

Multilayer Polymeric Nano composite Membrane for Oxygen Separation

2019 ◽  
Vol 1 (2) ◽  
pp. 1-11
Author(s):  
Gobi Nallathambi ◽  
Hazel Dhinakaran
Keyword(s):  
Polymer Concentration ◽  
Sio2 Nanoparticles ◽  
Air Separation ◽  
Regression Equations ◽  
Permeate Flux ◽  
Nano Composite ◽  
Box Behnken Design ◽  
Oxygen Selectivity ◽  
Multilayer Membrane ◽  
Spun Fiber

Air separation is a process of separating primary components from the atmospheric air. Development of membrane technologies plays a key role in air separation. Multi-layer polymeric nanocomposite membranes have been developed by a novel technique using Polyacrylonitrile (PAN) and cellulose acetate (CA) along with nano silica particles (SiO2) to obtain a higher oxygen selectivity and permeability. For the construction of the multilayer membrane, the Box-Behnken design has been used by employing three independent variables namely PAN Electro spinning time, the SiO2 percentage in the PAN polymer and CA/PEG polymer concentration. The developed membranes have been characterized for its surface morphology and physical properties. Along with the analysis of compound desirability, the results were also subject to statistical analysis in order to form regression equations. The electro spun fiber diameter increases along with the concentration of SiO2 nanoparticles and the range is from 50 nm to 400 nm. Moreover, the maximum pore size on the surface of the membrane lies between 200 to 400 nm whereas the maximum percentage of oxygen purity obtained is 48 with the permeate flux of 5.45 cm3/cm2/min.

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.

SINGLE-FACTOR LINEAR REGRESSION MODEL OF HODGKIN’S LYMPHOMA IN ADOLESCENTS

2017 ◽  
Vol 63 (2) ◽  
pp. 320-325
Author(s):  
Svetlana Kuleva ◽  
Svetlana Ivanova ◽  
Andrey Karitskiy ◽  
Darya Zvyagintseva
Keyword(s):  
Radiation Therapy ◽  
Linear Regression ◽  
Predictive Factors ◽  
Hodgkin’S Lymphoma ◽  
Risk Group ◽  
Hodgkin's Lymphoma ◽  
Regression Equations ◽  
Single Factor ◽  
Number Of Cycles ◽  
Selection Of

With the use of regression and dispersion analyzes conducted in this study it was possible to identify predictive factors that significantly worsen the prognosis of Hodgkin’s lymphoma in adolescents however constructed regression equations did not pass the quality assessment of the models, which did not allow them to be used for the construction of point and interval predictions. In a cohort of patients enrolled in the study a risk-adapted treatment program based on the risk group for stratification was conducted. Negative aspects of the results of our study could be related to the already selected volume of the program for these patients. In turn our analysis proves the validity of the selection of therapeutic loads (a number of cycles of polychemotherapy, doses of radiation therapy) depending on the risk group, into which the adolescent is stratified.

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