scholarly journals Fixed part of the model for breeding value estimation in pigs based on litter size

2007 ◽  
Vol 23 (5-6-1) ◽  
pp. 429-436
Author(s):  
D. Radojkovic ◽  
M. Petrovic ◽  
M. Mijatovic ◽  
C. Radovic
Keyword(s):  
Linear Regression ◽  
Fixed Effects ◽  
Statistical Significance ◽  
Least Square Method ◽  
Least Square ◽  
Breeding Value ◽  
Data Sets ◽  
Value Analysis ◽  
Applied Model ◽  
The Republic

The goal of this paper was to investigate the effect of various fixed effects on the number of born alive piglets in litter (NBA), based on results of Swedish Landrace sow fertility on three farms in Serbia, in order to determine the best adapted model for assessing genetic parameters and breeding value. Analysis of phenotipic variability of the NBA of Swedish Landrace sows was carried out based on fertility results on three swine farms (A, B and C) in the Republic of Serbia. Data sets encompassed reproduction indicators for 2803 (A), 1826 (B) and 2235 (C) sows, i.e. their 11014, 6757 and 8452 litters, respectively. For this analysis was used fix model of least square method which includes fixed effects of farrowing number, season of conception shown as combination of year and month, litter genotype, duration of previous period from weaning to conception, effect of sow age at farrowing like quadratic regression nested within farrowing number and linear regression influence of duration of previous lactation. The average NBA was within the interval from 9.13 (A) to 9.76 piglets (B and C). The monitored trait statistically highly significantly (p<0.001) varied under the effect of all systematic factors encompassed by the applied model, regardless of the source of analyzed data, Only the linear regression effect of duration of previous lactation for farm B was assessed as having lower statistical significance (p<0.05).

PENGARUH KNOWLEDGE MANAGEMENT, KOMPETENSI, MOTIVASI TERHADAP KINERJA KARYAWAN

2015 ◽  
Vol 5 (2) ◽  
pp. 1
Author(s):  
Miftahol Arifin
Keyword(s):  
Knowledge Management ◽  
Linear Regression ◽  
Significant Influence ◽  
Employee Performance ◽  
Least Square Method ◽  
Least Square ◽  
Analysis Tool ◽  
Ordinary Least Square ◽  
Competence Motivation ◽  
Performance Analyze

The purpose of this research is to analyze the influence of knowledge management on employee performance, analyze the effect of competence on employee performance, analyze the influence of motivation on employee performance). In this study, samples taken are structural employees PT.centris Kingdom Taxi Yogyakarta. The analysis tool in this study using multiple linear regression with Ordinary Least Square method (OLS). The conclusion of this study showed that the variables of knowledge management has a significant influence on employee performance, competence variables have an influence on employee performance, motivation variables have an influence on employee performance, The analysis showed that the variables of knowledge management, competence, motivation on employee performance.Keywords: knowledge management, competence, motivation, employee performance.

Fuzzy C-Regression Models

2013 ◽  
Vol 278-280 ◽  
pp. 1323-1326
Author(s):  
Yan Hua Yu ◽  
Li Xia Song ◽  
Kun Lun Zhang
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Linear Models ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Estimation Methods ◽  
Statistical Regression ◽  
Fuzzy Linear Regression ◽  
Fuzzy Degree

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.

scholarly journals Breeding value evaluation in Polish fur animals: Statistical description of fur coat and reproduction traits – relationship and inbreeding

2011 ◽  
Vol 49 (No. 1) ◽  
pp. 16-27 ◽  
Author(s):  
H. Wierzbicki ◽  
A. Filistowicz ◽  
W. Jagusiak
Keyword(s):  
Fixed Effects ◽  
Breeding Value ◽  
The Arctic ◽  
Arctic Fox ◽  
Data Sets ◽  
Value Evaluation ◽  
Inbreeding Coefficients ◽  
Silver Fox ◽  
Reproduction Traits ◽  
As Relationship

Three data sets were available: records on conformation and coat traits for the arctic fox from one farm (5 540 observations, collected between 1983 and 1997), and the same traits for the silver fox from three farms (8 199 observations, collected between 1984 and 1999). The third set comprised 5 829 observations on reproductive performance of the arctic fox from one farm, collected between 1984 and 1999. The GLM procedure was used to test the significance of fixed effects on the analysed reproduction traits as well as differences between groups. Phenotypic trends as well as relationship and inbreeding across the studied years were computed. Most of the phenotypic trends were positive. Low relationship and inbreeding coefficients in the arctic and silver fox populations under study were estimated. The average relationship coefficients for the silver and arctic fox populations were 0.015 and 0.010, respectively, whereas the average inbreeding coefficients for the same species were 0.0039 and 0.0016, respectively. No inbreeding was found in the arctic fox breeding females. &nbsp;

scholarly journals Modeling for determining the superiority of Holstein bulls as frozen semen producer and genetic source for milk production

2019 ◽  
Vol 44 (1) ◽  
pp. 47 ◽  
Author(s):  
A. Argiris ◽  
S. I. Santoso ◽  
Y. S. Ondho ◽  
E. Kurnianto
Keyword(s):  
Milk Production ◽  
Structural Equation ◽  
Least Square Method ◽  
Partial Least Square ◽  
Least Square ◽  
Breeding Value ◽  
Reproductive Efficiency ◽  
Genetic Traits ◽  
Frozen Semen ◽  
Holstein Bulls

The objective of this study was to develop models for determination the superiority of Holstein bulls as a producer of frozen semen and inheritance of the genetic traits of milk production. The ability of the bull to produce frozen semen per years was analyzed descriptively. Reproductive efficiency of frozen semen in artificial insemination was calculated by service per conception (S/C). Estimation sire breeding value for milk production was calculated by contemporary comparison (CC) method. Model of superiority bulls was analyzed by Structural Equation Model with Partial Least Square method (SEM-PLS). Total average production of frozen semen was 23,109±14,970 doses/year. The average S/C was 2.83. The CC value ranged from -1,865.7 until +1,636.3. Potency of milk production resulted from lactation cow offspring per bulls ranged from 951,749.2 to 52,347,822.9 liters per year. The economic value of bulls based on the potency milk production of offspring ranges from IDR 4,758,745,999 to IDR 261,739,114,505. The superiority of bulls was affected significantly (P<0.05) by frozen semen production, reproductive efficiency and average milk production of daughter cows (DC) as much as 0.59, -0.53 and 0.33, respectively. In conclusion, the superiority of bull can be explained about 78.3% by the production of frozen semen production, reproductive efficiency and milk production of offspring.

scholarly journals 3D Localization Algorithm Based on Linear Regression and Least Squares in NLOS Environments

2018 ◽  
Vol 11 (4) ◽  
pp. 1
Author(s):  
Jiang Li ◽  
Zhang Lei
Keyword(s):  
Linear Regression ◽  
Three Dimensional ◽  
Least Square Method ◽  
Mobile Terminal ◽  
Base Station ◽  
Least Square ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Positional Accuracy ◽  
The Relationship

Based on the positive bias property of the time of arrival(TOA) measurement error caused by the non-line-of-sight(NLOS) propagation, a simple and effective three dimensional(3D) geometrical localization algorithm was proposed, the algorithm needs no prior knowledge of time delay distribution of TOA, and only linear regression was used to estimate the parameters of the relationship between the NLOS distance error and the true distance, thus, the approximate real distance between mobile terminal (MT) and base station (BS) was reduced, then, the 3D geometric localization of mobile terminal was carried out by the least square method. The experimental results shows the effectiveness of the algorithm, and the positional accuracy is far higher than the required accuracy by E-911 in NLOS environments.

scholarly journals ANALISIS FAKTOR - FAKTOR YANG MEMPENGARUHI HARGA TANAH UNTUK PENGGUNAAN PERUMAHAN (STUDI KASUS: KECAMATAN BANYUMANIK)

2017 ◽  
Vol 5 (1) ◽  
pp. 57
Author(s):  
Triana Kurniwati ◽  
Bagio Mudakir
Keyword(s):  
Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Least Square Method ◽  
Research Area ◽  
Least Square ◽  
City Center ◽  
Land Price ◽  
Ordinary Least Square ◽  
The City

Semarang city is densely populated that demand of settlement will increase continually, but land in city center is very limited and even it is scarce, therefore the land price which is placed in city center is high. That is why many inhabitant of Semarang city prefer to live in outskirts of the city. The shifting of land demand to the outskirts is also followed by increasing of land price in outskirts, it causes the land price in outskirts is uncontrolled.The research takes location in Banyumanik area. This research area consists of 7 districts, that are Jabungan, Pudak Payung, Banyumanik, Srondol Kulon, Pedalangan, Ngesrep, and Gedawang district. The sample total is one hundred (100). The data is analyzed by using multiple linear regression model with ordinary least square method (OLS).

scholarly journals PENGARUH PENYALURAN DANA BANK KONVENSIONAL DAN BANK SYARIAH TERHADAP PRODUK DOMESTIK BRUTO DI INDONESIA

Media Ekonomi ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 127
Author(s):  
Sinta Rani Siti Sarah ◽  
Sumiyarti ,
Keyword(s):  
Linear Regression ◽  
Gross Domestic Product ◽  
Least Square Method ◽  
Least Square ◽  
Domestic Product ◽  
Islamic Banks ◽  
Ordinary Least Square ◽  
Analysis Technique ◽  
Using Data ◽  
Conventional Banks

<p><em>This study aims to analyse the distribution of Islamic banks and the distribution of conventional bank funds to the gross domestic product in Indonesia. The analysis was carried out using data scanned by the Central Statistics Agency (BPS) and Bank Indonesia for 2004: 01-2014: 04 period. The analysis technique used in this study was Multiple Linear Regression using the OLS (Ordinary Least Square) method. The results showed that the distribution of Islamic banks had a positive and not significant effect on the growth of Gross Domestic Product (GDP), while the distribution of funds from conventional banks and Islamic banks was significant towards Gross Domestic Product.</em></p>

scholarly journals A linear regression approach in the determination of work standards for a manufacturing organisation

2007 ◽  
Vol 25 (1) ◽  
pp. 30
Author(s):  
S.A. Oke
Keyword(s):  
Linear Regression ◽  
Least Square Method ◽  
Least Square ◽  
Manufacturing Plants ◽  
Scientific Investigations ◽  
Manufacturing Operations ◽  
Penalty Costs ◽  
Production Manager ◽  
Established Technique

In semi-automated roofing sheets manufacturing plants, production managers receive large orders, which most often, are to be delivered within scheduled delivery dates; failure to deliver orders incurs penalty costs and litigation charges. The challenge therefore for the production manager is to be able to predict product completion period and map available labour man-hours to production of roofing sheet orders. This paper presents a linear regression model for setting up work standards for a roofing sheet manufacturing plant. Linear regression is a relatively established technique in scientific investigations, but new in its applied form to work standards, particularly in roofing sheets manufacturing operations standards setting. The accuracy of the model was determined by the least square method, and the result suggests the feasibility of applying a model in the case presented. Thus, the contribution of this paper lies in the application of a known technique in a new area. The utility of the tool is in its ability to provide useful information for production planning and implementation purposes in the roofing sheets plants.

scholarly journals Health Outcomes Before, During and After the Great Recession in Canada: A Longitudinal Analysis

2020 ◽  
Vol 12 (1) ◽  
pp. 59-72
Author(s):  
Ehsan Latif
Keyword(s):  
Health Status ◽  
Great Recession ◽  
Fixed Effects ◽  
Least Square Method ◽  
Least Square ◽  
The Great Recession ◽  
Reported Health ◽  
Self Reported Health Status ◽  
Probit Method ◽  
Panel Fixed Effects

Using panel data from Canadian National Population Health Survey (2006-2011), this study examined what happened to individuals’ self-reported health during and in the aftermath of great recession of 2008-2009. The study used different methods such as ordered probit method, ordinary least square method and panel fixed effects method. Once individual specific fixed effects are controlled for, the results show that great recession had no statistically significant detrimental impact on self-reported health status. The results further show that health status in the aftermath of great recession did not significantly differ from the health status before the great recession.

Computer Aided Regression Analysis of Synergistic Effect of Energy Industry

2014 ◽  
Vol 543-547 ◽  
pp. 4667-4670
Author(s):  
Jiong Wei Chen ◽  
Guo Ping Cheng
Keyword(s):  
Economic Development ◽  
Regression Analysis ◽  
Linear Regression ◽  
Synergistic Effect ◽  
Linear Correlation ◽  
Least Square Method ◽  
Least Square ◽  
Energy Industry ◽  
Computer Aided ◽  
Industry Investment

In this paper, we try to find out the synergistic effect between energy industry investment and economic development. Based on the objective, with computer aided method, we choose the statistic data of energy industry investment and GDP of China from 2001 to 2011, use econometrics software Eviews 5.0 and least square method to build the linear regression model between energy industry investment and GDP. The result shows that there exists a linear correlation between energy industry investment and GDP; moreover, energy industry investment is more influential than the GDP.

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