scholarly journals Modeling of temporal development of population taking into account the situation of municipalities in the resettlement system (according to the example of the Tyumen Region)

2020 ◽  
Vol 26 (1) ◽  
pp. 215-227
Author(s):  
V. Dobryakova ◽  
A. Dobryakov
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Spatial Statistics ◽  
Network Data ◽  
Regression Equations ◽  
Temporal Development ◽  
Data Set ◽  
Regional Center ◽  
Definition Of ◽  
The Relationship

The work is devoted to application of spatial statistics and regression analysis tools in the ArcGIS Pro program. In this report we try to confirm two theories in the relationship between positional characteristics of municipalities and the temporal development of population: The farther the locality is from the main settlement of the territory, the faster it loses its own population. The farther the locality is from the main highways of the territory, the faster it loses its own population. The main aim of this article is to find the strictest definition of the type of correlation between such specific distances as the distance to the regional center, the distance to the nearest highway and the relative changes in the municipalities’ population, according to the example of the Tyumen region. A network data set was created to calculate the distances, it contains several elements: main roads, calculated centers of municipalities (CM), lines — distances from centers to the nearest road (“stops”). For the study we used information on changes of population for 4 periods: 1981–1990, 1990–2002, 2002–2010 and 2010–2018. The dependence was done by enumerating the degrees of distances. We considered that the dependence was selected in case the relevant correlation coefficient was the largest. For each chosen relationship, ArcGIS Pro performed a complete statistical analysis, based on the results, the significance of the model was identified, residual maps constructed, and regression equations calculated. All the models except the first period turned out to be significant, but they were displaced, which indicates the existence of some unexplored factors. In the context of the constructed models, it was assumed that the distance to the regional center is closely connected with an expansion of the population in the surrounding municipalities, but the expansion gets more the closer the municipal district is to Tyumen. The distance to the nearest highway is associated with a decrease of population, and the farther the municipality is from the highway, the more it loses population.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

Regression Analysis on Influences of Hem Parameters on Flare Sagging of Semi-Circular Skirt

2011 ◽  
Vol 331 ◽  
pp. 594-598
Author(s):  
Hong Ni
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Measured Data ◽  
Silk Fabric ◽  
Linear Regression Equation ◽  
Analysis Software ◽  
Wool Fabrics ◽  
Object Of Study ◽  
The Relationship ◽  
Statistical Analysis Software

Select 45 pieces of silk, cotton and wool fabrics in total, with semi-circular skirt modeling as object of study, investigate the relationship between flare sagging in straight & inclined grains of skirt pieces and fabric types, analyze the influence of hem parameters on flare sagging of semi-circular skirt and obtain multiple linear regression equation by disposing the measured data with SPSS statistical analysis software. The study result shows that the skirt hem of silk fabric is sagging more significantly than that of cotton and wool fabrics and there is a multi-linear relationship between semi-circular flare sagging and parameters.The research of this subject has both theoretical value and practical value.

Effect of Ultrasonography in the Assessment of Carotid Artery Stenosis

Vascular ◽  
2005 ◽  
Vol 13 (1) ◽  
pp. 28-33 ◽  
Author(s):  
Sergio X. Salles-Cunha ◽  
Enrico Ascher ◽  
Anil P. Hingorani ◽  
Natalia Markevich ◽  
Richard W. Schutzer ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Internal Carotid Artery ◽  
Carotid Artery Stenosis ◽  
Internal Carotid ◽  
Artery Stenosis ◽  
Regression Equations ◽  
Velocity Data ◽  
Data Set ◽  
Natural Logarithm ◽  
The Relationship

Although ultrasonography (US) advantageously portrays lumen and wall thickness, velocity criteria have been used primarily to interpret carotid artery stenosis. The relationship of US and velocity measurements was investigated. Peak-systolic and end-diastolic velocities (PSV, EDV) increase exponentially as the lumen of the internal carotid artery narrows and the percent stenosis (%S) increases. We tested the consistency of the relationship between carotid velocities and US %S in two distinct data sets. One data set was used to obtain regression equations relating velocity parameters and %S based on US. Validation of these equations was conducted using a separate, independent data set. US measurements were classified in 12 %S intervals. PSV, EDV, the ratio of the internal carotid artery to the common carotid artery PSV, and %S were entered consecutively until 10 records for each %S interval were obtained. Regression equations obtained in the first data set were used to predict %S in the second data set. Predicted %S was then compared with actual US %S. The highest correlation in the first data set ( r = .89) was between %S and the natural logarithm (ln) of PSV. This ln PSV -%S equation was then applied to a second data set of an additional 120 carotid duplex images. In the second data set, actual %S and PSV–predicted %S differed by > 10% in 38 cases (32%). When all velocity-%S regression equations were used for comparison, differences between actual and at least one velocity-predicted %S were > 10% in 19% of the arteries. Conversely, actual %S matched at least one prediction of %S based on velocity data in 81% of the cases. US %S differed significantly from single velocity-based estimates of %S in at least one-third of the cases. On the other hand, four of five US measurements were confirmed by at least one velocity parameter. Emphasis on US, in addition to velocity data, is recommended for the interpretation of duplex US carotid examinations.

Proton NMR Analysis of Octane Number for Motor Gasoline: Part IV

1992 ◽  
Vol 46 (8) ◽  
pp. 1294-1300 ◽  
Author(s):  
M. Ichikawa ◽  
N. Nonaka ◽  
H. Amano ◽  
I. Takada ◽  
S. Ishimori ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Aromatic Compounds ◽  
Octane Number ◽  
Proton Magnetic Resonance ◽  
Linear Regression Analysis ◽  
Regression Equations ◽  
Nmr Analysis ◽  
Motor Gasoline ◽  
The Relationship

Software (a program) for predicting the octane number of motor gasoline by proton magnetic resonance (PMR) spectrometry has been formulated. At the same time, a method has been studied to predict the composition of gasoline (in terms of the contents of paraffin, olefin, and aromatic compounds). The formulated program was evaluated by using it to predict the octane numbers of 31 samples of marketed summer gasoline (including 16 regular and 15 premium products), whose octane numbers and compositions were identified according to the ASTM standards. Also, the relationship between the PMR spectrum and gasoline composition was subjected to linear regression analysis by using the 31 samples whose octane numbers were calculated, and the appropriateness of the resultant regression equations was assessed. This report concerns the results of the study in which the octane numbers of the 31 samples were satisfactorily predicted by the formulated program and useful linear regression equations were obtained for the prediction of the composition of gasoline.

scholarly journals Economic Growth : The Impact of Zakat Funds and Tax on Business Capital

IKONOMIKA ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 141-156
Author(s):  
Sri Dewi Anggadini (Universitas Komputer, Indonesia) ◽  
Surtikanti Surtikanti (Universitas Komputer, Indonesia) ◽  
Faez M. Hassan (Mustansiriyah University, Iraq)
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Statistical Analysis ◽  
Data Processing ◽  
Multiple Regression Analysis ◽  
Distribution Data ◽  
Regression Equations ◽  
West Java ◽  
Local Taxes ◽  
The Impact

This study aims to determine the effect of Zakat Funds and Tax on Business Capitales on Economic Growth. The population in this study is the data of the Province of West Java from 2010 to 2017 where the economic growth report, Tax on Business Capital report and zakat fund distribution report are used.   The sample taken by the author in this study is the Zakat Fund Distribution Data, Tax on Business Capital Data and the Gross Regional Domestic Product (PDRB) data of West Java Province from 2010 to 2017. Researchers used multiple statistical analysis and correlation methods. To obtain more accurate results in multiple regression analysis, classic assumption testing is executed so that the results obtained are regression equations. The results of the study show that the Zakat Fund Distribution and Tax on Business Capital data have a significant effect on economic growth. Based on data processing, it shows that the distribution of zakat funds and local taxes simultaneously in providing an influence on economic growth variables of 76%. While the rest of 100% - 76% = another 24%  is the influence of other variables not examined in this study.Keywords : Zakat Funds; Tax on Business Capital; Economic Growth

scholarly journals Relationship between Water Activity and Moisture Content in Floral Honey

Foods ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 30 ◽  
Author(s):  
Chiachung Chen
Keyword(s):  
Regression Analysis ◽  
Moisture Content ◽  
Linear Equation ◽  
Water Activity ◽  
T Test ◽  
Regression Equations ◽  
Collection Site ◽  
Factors Affecting ◽  
Regression Parameters ◽  
The Relationship

The water activity (Aw) and moisture content (MC) data of floral honey at five temperatures were determined using the Aw method and it was found that temperature significantly affected the Aw/MC data. The linear equation could be used to express the relationship between Aw and MC of honeys. The empirical regression equations between parameters and temperature were established. To evaluate the factors affecting the Aw/MC data, we used categorical tests of regression analysis to assess the effect of the correlation between Aw and MC of honey and examined the factors affecting the regression parameters. Six datasets from five countries were selected from the literature. The significance of the levels of qualitative categories was tested by t-test. The slope of the relationship between Aw and MC was affected by the state of honey (liquid and crystallized). The intercepts were significantly affected by honey type (flower or honeydew), harvesting year, geographical collection site, botanical source and other factors. The outliers in the datasets significantly affected the results. With modern regression analysis, useful information on the correlation between Aw and MC could be found. The results indicated that no universal linear equation for Aw and MC could be used. The Aw value could be used as a criterion for the honey industry; then, the MC of honey could be calculated by the specific linear equation between Aw and MC.

A probabilistic modeling approach for interpretable data inference and classification

2020 ◽  
pp. 1-17
Author(s):  
Shuaiyu Yao ◽  
Jian-Bo Yang ◽  
Dong-Ling Xu
Keyword(s):  
Statistical Analysis ◽  
Probabilistic Modeling ◽  
Data Set ◽  
Inference Mechanism ◽  
Modeling Approach ◽  
Input Variables ◽  
Data Inference ◽  
The Relationship ◽  
Better Than ◽  
Iris Data

In this paper, we propose a new probabilistic modeling approach for interpretable inference and classification using the maximum likelihood evidential reasoning (MAKER) framework. This approach integrates statistical analysis, hybrid evidence combination and belief rule-based (BRB) inference, and machine learning. Statistical analysis is used to acquire evidence from data. The BRB inference is applied to analyze the relationship between system inputs and outputs. An interdependence index is used to quantify the interdependence between input variables. An adapted genetic algorithm is applied to train the models. The model established by the approach features a unique strong interpretability, which is reflected in three aspects: (1) interpretable evidence acquisition, (2) interpretable inference mechanism, and (3) interpretable parameters determination. The MAKER-based model is shown to be a competitive classifier for the Banana, Haberman’s survival, and Iris data set, and generally performs better than other interpretable classifiers, e.g., complex tree, logistic regression, and naive Bayes.

Topic-marking prepositions in Swedish: A corpus-based analysis of adpositional synonymy

2014 ◽  
Vol 37 (2) ◽  
pp. 257-296 ◽  
Author(s):  
Anton Granvik ◽  
Susanna Taimitarha
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Initial Position ◽  
The Other ◽  
Data Set ◽  
Multinomial Logistic Regression Analysis ◽  
Usage Patterns ◽  
Head Element ◽  
The Relationship

This study analyses the relationship between four near-synonymous Swedish prepositions, namely angående, beträffande, gällande and rörande, which are used to establish what we call a topic-marking relation, as in statens avtal angående finansieringen ‘the agreement of the state regarding the financing’. By focusing on a single, loosely defined genre consisting of the written texts included in the Swedish PAROLE corpus, we address the question of what differences there are among these four prepositions, which intuitively seem highly similar and mutually interchangeable. In order to find out which contextual and grammatical factors might influence the choice of one preposition over the others, two complementary analyses were performed. First, a so-called collostructional analysis (see Stefanowitsch & Gries 2003, Gries & Stefanowitsch 2004) was performed on 791 cases of these prepositions found in the PAROLE corpus. Secondly, the corpus examples were annotated according to ten syntactic and four semantic criteria and a multinomial logistic regression analysis was performed on the annotated data set. The results show some tendencies pointing to differing usage patterns of the four prepositions. Beträffande stands out as the most frequent of them all and is also preferably used when no explicit head element is present, typically in sentence-initial position. Angående prefers words of communication while rörande is used when another topic-marking preposition is also present. On the other hand, neither of the two analyses leads to a clear distinction among the four prepositions, thus pointing to the fact that these topic-marking prepositions indeed constitute a fairly good case of adpositional synonymy, with few distinguishing factors separating one from the other.

scholarly journals Use of Modern Regression Analysis in the Dielectric Properties of Foods

Foods ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1472
Author(s):  
Yu-Kai Weng ◽  
Jiunyuan Chen ◽  
Ching-Wei Cheng ◽  
Chiachung Chen
Keyword(s):  
Regression Analysis ◽  
Dielectric Properties ◽  
Influencing Factors ◽  
Polynomial Regression ◽  
Treatment Method ◽  
Regression Equations ◽  
Constant Variance ◽  
Dependent Variables ◽  
Qualitative Variables ◽  
The Relationship

The dielectric properties of food materials is used to describe the interaction of foods with electromagnetic energy for food technology and engineering. To quantify the relationship between dielectric properties and influencing factors, regression analysis is used in our study. Many linear or polynomial regression equations are proposed. However, the basic assumption of the regression analysis is that data with a normal distribution and constant variance are not checked. This study uses sixteen datasets from the literature to derive the equations for dielectric properties. The dependent variables are the dielectric constant and the loss factor. The independent variables are the frequency, temperature, and moisture content. The dependent variables and frequency terms are transformed for regression analysis. The effect of other qualitative factors, such as treatment method and the position of subjects on dielectric properties, are determined using categorical testing. Then, the regression equations can be used to determine which influencing factors are important and which are not. The method can be used for other datasets of dielectric properties to classify influencing factors, including quantitative and qualitative variables.

Statistical analysis and definition of blockages-prediction formulae for the wastewater network of Oslo by evolutionary computing

2009 ◽  
Vol 59 (8) ◽  
pp. 1457-1470 ◽  
Author(s):  
Rita Ugarelli ◽  
Stig Morten Kristensen ◽  
Jon Røstum ◽  
Sveinung Sægrov ◽  
Vittorio Di Federico
Keyword(s):  
Statistical Analysis ◽  
Polynomial Regression ◽  
Physical Phenomenon ◽  
Capital City ◽  
Data Set ◽  
Explanatory Variables ◽  
Technical Performance ◽  
Evolutionary Polynomial Regression ◽  
Definition Of ◽  
And Function

Oslo Vann og Avløpsetaten (Oslo VAV)—the water/wastewater utility in the Norwegian capital city of Oslo–is assessing future strategies for selection of most reliable materials for wastewater networks, taking into account not only material technical performance but also material performance, regarding operational condition of the system. The research project undertaken by SINTEF Group, the largest research organisation in Scandinavia, NTNU (Norges Teknisk-Naturvitenskapelige Universitet) and Oslo VAV adopts several approaches to understand reasons for failures that may impact flow capacity, by analysing historical data for blockages in Oslo. The aim of the study was to understand whether there is a relationship between the performance of the pipeline and a number of specific attributes such as age, material, diameter, to name a few. This paper presents the characteristics of the data set available and discusses the results obtained by performing two different approaches: a traditional statistical analysis by segregating the pipes into classes, each of which with the same explanatory variables, and a Evolutionary Polynomial Regression model (EPR), developed by Technical University of Bari and University of Exeter, to identify possible influence of pipe's attributes on the total amount of predicted blockages in a period of time. Starting from a detailed analysis of the available data for the blockage events, the most important variables are identified and a classification scheme is adopted. From the statistical analysis, it can be stated that age, size and function do seem to have a marked influence on the proneness of a pipeline to blockages, but, for the reduced sample available, it is difficult to say which variable it is more influencing. If we look at total number of blockages the oldest class seems to be the most prone to blockages, but looking at blockage rates (number of blockages per km per year), then it is the youngest class showing the highest blockage rate. EPR allowed identifying the relation between attitude to block and pipe's attributes in order to understand what affects the possibility to have a blockage in the pipe. EPR provides formulae to compute the accumulated number of blockages for a pipe class at the end of a given period of time. Those formulae do not represent simply regression models but highlight those variables which affect the physical phenomenon in question.

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