scholarly journals EFEITO DO MEIO E DA IDADE DA VACA SOBRE O GANHO DE PESO NA FASE DE CRIA, RECRIA E OS DIAS PARA SE OBTER 160 KG EM ANIMAIS DA RAÇA GUZERÁ

2004 ◽  
Vol 9 (1) ◽  
Author(s):  
E. GEMIN ◽  
J.C. SOUZA ◽  
L.O.C. SILVA ◽  
C.H.M. MALHADO ◽  
P.B. FERRAZ FILHO
Keyword(s):  
Environmental Factors ◽  
Statistical Model ◽  
Least Squares ◽  
Random Effects ◽  
Environmental Effects ◽  
Fixed Effects ◽  
Least Squares Method ◽  
Data Set ◽  
Quadratic Effect ◽  
Daily Gain

O objetivo deste trabalho foi avaliar a influência dos efeitos de meio e da idade da vaca sobre os ganhos de peso do nascimento ao desmame (GPD), período pós-desmame (GPS) e sobre o número de dias para se obter 160 kg (D160). O rebanho avaliado continha 1.747 animais, sendo os dados analisados pelo método dos quadrados mínimos utilizando-se um modelo estatístico contendo os efeitos fixos de mês, ano e sexo do bezerro, o efeito aleatório de touros na fazenda, e como covariável a idade da vaca ao parto. As médias ajustadas para ganho de peso pré e pós-desmame, e para dias para a obtenção 160 kg foram 0,604 ± 0,01 kg; 0,399 ± 0,01 kg; em 285 ± 5,3 dias, respectivamente. Os machos foram superiores às fêmeas relativo ao GPD = 6,0%; D160 = 5,8 %, GPS = 20,1%. Quanto ao mês, as maiores médias de ganho de peso no pré-desmame recaiu nos animais nascidos no mês de agosto. Com relação aos dias para se obter 160 kg, os melhores resultados foram dos animais nascidos nos meses julho a setembro. A idade da vaca influenciou as caracteristicas ganho de peso pré-desmame e no D160. Environmental effects and age of dam on pre- and post-weaning daily gain, and on number of days to gain 160 kg from birth to weaning on guzerath breed cattle Abstract The objective of this study was to evaluate the effects of environmental factors and age of dam on pre- (GPD) and post-weaning (GPS) daily gain, and on the were number of days to gain 160 kg (D160) from birth to weaning. The data set contained 1,747 animals, and were analyzed by the least squares method. The statistical model included the fixed effects of month and year of birth, and sex of the calf and age of the dam at calving. Sire nested within farm and the error were random effects. The pre- and post-weaning average daily gains, and days to gain 160 kg least squares means were 0.604 ± 0.01 kg, 0.399 ± 0.01 kg, and 285.0 ± 5.3 days, respectively. The males were 6.0, 21.1 and 5.8% superior to the females for GPD, GPS and D160, respectively. The highest pre-weaning gain was for the animals born August. Regarding D160, the best results were for the animals born from July to September. Age of the cow showed a significant quadratic effect on the traits. The best cows were the 94-month-old ones. First calving cows produced the lightest calves. The results showed the importance of the environmental effects on the traits studied, evidencing the need for them to be corrected.

Intergenerational Earnings Mobility in Italy

2007 ◽  
Vol 7 (2) ◽  
Author(s):  
Sauro Mocetti
Keyword(s):  
Labor Market ◽  
Least Squares ◽  
Household Income ◽  
Intergenerational Mobility ◽  
Least Squares Method ◽  
Developed Countries ◽  
Data Set ◽  
Labor Market Success ◽  
Term Labor

Abstract This paper contributes to the growing number of studies on intergenerational mobility by providing a measure of earnings elasticity for Italy. The absence of an appropriate data set is overcome by adopting the two-sample two-stage least squares method. The analysis, based on the Survey of Household Income and Wealth, shows that intergenerational mobility is lower in Italy than it is in other developed countries. We also examine the reasons why the long-term labor market success of children is related to that of their fathers.

Incorrect least-squares regression coefficients in method-comparison analysis.

1979 ◽  
Vol 25 (3) ◽  
pp. 432-438 ◽  
Author(s):  
P J Cornbleet ◽  
N Gochman
Keyword(s):  
Standard Deviation ◽  
Least Squares ◽  
Least Squares Method ◽  
Regression Line ◽  
Method Comparison ◽  
Regression Coefficients ◽  
Least Squares Regression ◽  
Data Set ◽  
Data Points ◽  
Regression Slopes

Abstract The least-squares method is frequently used to calculate the slope and intercept of the best line through a set of data points. However, least-squares regression slopes and intercepts may be incorrect if the underlying assumptions of the least-squares model are not met. Two factors in particular that may result in incorrect least-squares regression coefficients are: (a) imprecision in the measurement of the independent (x-axis) variable and (b) inclusion of outliers in the data analysis. We compared the methods of Deming, Mandel, and Bartlett in estimating the known slope of a regression line when the independent variable is measured with imprecision, and found the method of Deming to be the most useful. Significant error in the least-squares slope estimation occurs when the ratio of the standard deviation of measurement of a single x value to the standard deviation of the x-data set exceeds 0.2. Errors in the least-squares coefficients attributable to outliers can be avoided by eliminating data points whose vertical distance from the regression line exceed four times the standard error the estimate.

Prestack imaging of seismic data using Lp iterative reweighted least-squares wavefield extrapolation filters in the frequency-space domain

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. V243-V252
Author(s):  
Wail A. Mousa
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Least Squares Method ◽  
Filter Design ◽  
Finite Impulse Response ◽  
Weighted Least Squares ◽  
Data Set ◽  
Frequency Space ◽  
Wavefield Extrapolation ◽  
Iterative Reweighted Least Squares

A stable explicit depth wavefield extrapolation is obtained using [Formula: see text] iterative reweighted least-squares (IRLS) frequency-space ([Formula: see text]-[Formula: see text]) finite-impulse response digital filters. The problem of designing such filters to obtain stable images of challenging seismic data is formulated as an [Formula: see text] IRLS minimization. Prestack depth imaging of the challenging Marmousi model data set was then performed using the explicit depth wavefield extrapolation with the proposed [Formula: see text] IRLS-based algorithm. Considering the extrapolation filter design accuracy, the [Formula: see text] IRLS minimization method resulted in an image with higher quality when compared with the weighted least-squares method. The method can, therefore, be used to design high-accuracy extrapolation filters.

scholarly journals The algorithm of Bayesian estimation of maternal genetic and permanent maternal environmental variances in a two-trait binary threshold model

2011 ◽  
Vol 49 (No. 2) ◽  
pp. 58-63
Author(s):  
E. Skotarczak ◽  
M. Szyd ◽  
A. Dobek ◽  
K. Moli ◽  
T. Szwaczkowski
Keyword(s):  
Bayesian Estimation ◽  
Gibbs Sampling ◽  
Random Effects ◽  
Environmental Effects ◽  
Fixed Effects ◽  
Threshold Model ◽  
Sampling Procedure ◽  
Numerical Example ◽  
Estimation And Prediction

The paper presents an algorithm for the estimation and prediction of parameters in a two-trait binary threshold model. The model includes fixed effects and the following random effects: genetic direct additive, genetic maternal additive and permanent maternal environmental effects. The Gibbs sampling procedure was used to estimate the parameters. The algorithm was illustrated with a numerical example showing appropriateness of the proposed method.  

Effect of genetic and non-genetic factors on age at first calving in Sahiwal cattle

2016 ◽  
Author(s):  
Jitendra Singh ◽  
V. K. Singh ◽  
Alok Kumar Yadav ◽  
Amit Kumar Jha
Keyword(s):  
Statistical Model ◽  
Least Squares ◽  
Genetic Improvement ◽  
Fixed Effects ◽  
Genetic Factors ◽  
Uttar Pradesh ◽  
Heritability Estimate ◽  
Age At First Calving ◽  
Sahiwal Cows ◽  
Selection Of

The present study was conducted on Sahiwal cows maintained at Uttar Pradesh Livestock- cum- Agriculture Farm, Chak Ganjaria, Lucknow. A total of 1194 records on age at first calving (AFC) spanning over a period of 57 years (1949 to 2006) were subjected to least squares analysis using suitable statistical model considering sire as random while period and season as fixed effects. The least squares mean of AFC was estimated to be 1251.77± 22.15 days. The least squares analysis revealed significant effect (P £ 0.01) of sire and period. However, the effect of season was found to be non-significant. The heritability estimate of age at first calving was found to be 0.159. The genetic, phenotypic and environmental trend for AFC were -3.31, 32.78 and 36.09 respectively. It was concluded from the present findings that selection of sire may be practiced for genetic improvement of this trait and ameliorative managemental practices should be employed to improve upon the trait i.e. age at first calving.

Determinants of SME growth

2016 ◽  
Vol 39 (9) ◽  
pp. 966-986 ◽  
Author(s):  
Habib Kachlami ◽  
Darush Yazdanfar
Keyword(s):  
Random Effects ◽  
Financial Institutions ◽  
Significant Influence ◽  
Fixed Effects ◽  
Explanatory Power ◽  
Ordinary Least Squares ◽  
Firm Level ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to study the firm-level financial variables affecting the growth of small and medium-sized enterprises (SMEs). Design/methodology/approach The study applies a resource-based view to analyze the firm-level as well as industry-level determinants of SME growth. Empirical evidence has also been provided from a data set of SMEs in Sweden to support the hypotheses. For a robust statistical analysis, three models – ordinary least squares (OLS) regression, random-effects regression and fixed-effects regression – are used to examine the influence of explanatory variables on growth. Findings The findings of this study show a positive and significant influence of profitability, short-term debt and size on a firm’s growth across all three models. Results regarding the influence of long-term debt on growth, however, are mixed. While the results of a fixed-effect model show the negative and significant influence of long-term debt on growth, the results according to OLS and random effects show long-term debt positively related to growth. Research limitations/implications This study has been conducted over a period of four years and in the context of Sweden which may limit the generalizability of its results for longer periods and for different contexts. Moreover, the low explanatory power of the models implies the need to also consider other types of variables, such as managerial or socio-economic variables, to better explain the determinants of SME growth. Practical implications Understanding the determinants of growth can be important for policy makers, SME managers and financial institutions. The findings of this study can be used for designing policies which stimulate SME growth. Realizing the financial resources that influence growth can also help SME managers and financial institutions to understand each other’s need for better cooperation. Originality/value This paper applies different models for analyzing large and cross-sectoral data regarding SME growth in the context of Sweden.

Breed and environmental effects on lamb production in Nigeria

1981 ◽  
Vol 96 (1) ◽  
pp. 9-15 ◽  
Author(s):  
V. Buvanendran ◽  
I. F. Adu ◽  
B. A. Oyejola
Keyword(s):  
Body Weight ◽  
Environmental Factors ◽  
Least Squares ◽  
Correlation Coefficient ◽  
Environmental Effects ◽  
Correlation Coefficients ◽  
Correction Factors ◽  
The Cross ◽  
Highly Correlated ◽  
Least Squares Estimates

SUMMARYTwo indigenous breeds of sheep in Nigeria, the Yankasa and Uda and crosses of these with exotic breeds, were evaluated for lamb weights at birth, 3 months and 6 months of age and for adult ewe weight. The cross-bred lambs were significantly (P < 0·05) heavier than the indigenous breeds at all ages. Differences among the indigenous breeds were not significant. Mature ewe weight was 40·8 kg in the cross-bred and 36·0 and 31·1 kg in the Uda and Yankasa respectively, differences between all breeds being significant (P <0·05). Lamb productivity (lamb weight per kg of ewe metabolic body weight) estimates demonstrated that the differences between breeds were small.Least-squares estimates of effects of environmental factors on lamb performance showed that type of birth and age of dam were important for lamb weights at the three ages. Season and sex also had significant effects on birth and 6-month weights respectively. Correction factors for lamb weights were derived from least-squares estimates.The correlation coefficient between birth and 3-month weight was significant in all breeds and ranged from 0·39 to 0·55. Three-month and 6-month weights were highly correlated with estimates of correlation coefficients ranging from 0·71 to 0·74. Repeatability estimates of birth, 3·month, 6·month and ewe weights, all as traits of the ewe in the Yankasa, were 0·25, 0·21, 0·09 and 0·48, respectively.

scholarly journals Comparison of Competing Approaches to Analyzing Cross-Classified Data: Random Effects Models, Ordinary Least Squares, or Fixed Effects with Cluster Robust Standard Errors

2021 ◽  
Author(s):  
Young Ri Lee ◽  
James E Pustejovsky
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Good Alternative ◽  
Ordinary Least Squares ◽  
Alternative Methods ◽  
Least Squares Regression ◽  
Monte Carlo Simulation Study ◽  
Random Effects Models ◽  
Fixed Effects Regression

Cross-classified random effects modeling (CCREM) is a common approach for analyzing cross-classified data in education. However, when the focus of a study is on the regression coefficients at level one rather than on the random effects, ordinary least squares regression with cluster robust variance estimators (OLS-CRVE) or fixed effects regression with CRVE (FE-CRVE) could be appropriate approaches. These alternative methods may be advantageous because they rely on weaker assumptions than what is required by CCREM. We conducted a Monte Carlo Simulation study to compare the performance of CCREM, OLS-CRVE, and FE-CRVE in models with crossed random effects, including conditions where homoscedasticity assumptions and exogeneity assumptions held and conditions where they were violated. We found that CCREM performed the best when its assumptions are all met. However, when homoscedasticity assumptions are violated, OLS-CRVE and FE-CRVE provided similar or better performance than CCREM. FE-CRVE showed the best performance when the exogeneity assumption is violated. Thus, we recommend two-way FE-CRVE as a good alternative to CCREM, particularly if the homoscedasticity or exogeneity assumptions of the CCREM might be in doubt.

scholarly journals Effects of environmental factors on multiple ovulation of zebu donors

2006 ◽  
Vol 58 (4) ◽  
pp. 567-574 ◽  
Author(s):  
M.G.C.D. Peixoto ◽  
J.A.G. Bergmann ◽  
C.G. Fonseca ◽  
V.M. Penna ◽  
C.S. Pereira
Keyword(s):  
Environmental Factors ◽  
Least Squares ◽  
Inbreeding Coefficient ◽  
Corpora Lutea ◽  
Data Sets ◽  
Data Set ◽  
The Third ◽  
Multiple Ovulation ◽  
The Mean ◽  
Best Responses

Data on 1,294 superovulations of Brahman, Gyr, Guzerat and Nellore females were used to evaluate the effects of: breed; herd; year of birth; inbreeding coefficient and age at superovulation of the donor; month, season and year of superovulation; hormone source and dose; and the number of previous treatments on the superovulation results. Four data sets were considered to study the influence of donors’ elimination effect after each consecutive superovulation. Each one contained only records of the first, or of the two firsts, or three firsts or all superovulations. The average number of palpated corpora lutea per superovulation varied from 8.6 to 12.6. The total number of recovered structures and viable embryos ranged from 4.1 to 7.3 and from 7.3 to 13.8, respectively. Least squares means of the number of viable embryos at first superovulation were 7.8 ± 6.6 (Brahman), 3.7 ± 4.5 (Gyr), 6.1 ± 5.9 (Guzerat) and 5.2 ± 5.9 (Nellore). The numbers of viable embryos of the second and the third superovulations were not different from those of the first superovulation. The mean intervals between first and second superovulations were 91.8 days for Brahman, 101.8 days for Gyr, 93.1 days for Guzerat and 111.3 days for Nellore donors. Intervals between the second and the third superovulations were 134.3, 110.3, 116.4 and 108.5 days for Brahman, Gyr, Guzerat and Nellore donors, respectively. Effects of herd nested within breed and dose nested within hormone affected all traits. For some data sets, the effects of month and order of superovulation on three traits were importants. The maximum number of viable embryos was observed for 7-8 year-old donors. The best responses for corpora lutea and recovered structures were observed for 4-5 year-old donors. Inbreeding coefficient was positively associated to the number of recovered structures when data set on all superovulations was considered.

scholarly journals Impact of Full IFRS, Accounting Standards for SMES and Company Demographics on Firms’ Return on Asset and Return on Equity using Panel Data Regression

2019 ◽  
Vol 8 (6S) ◽  
pp. 589-601 ◽  
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Ordinary Least Squares ◽  
Lagrangian Multiplier ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Real Property ◽  
The Impact

Due to globalization, markets are becoming more interconnected as the companies are engaged in doing cross-border offerings. Currently, competitions are intensified because Domestic organizations discover themselves competing with each nearby opposite numbers and worldwide companies. But one component that hinders SMEs is the need for reliable and similar monetary data. According to Abarca (2014), adoption of a high-quality and consistent set of accounting requirements is critical so as for the businesses to remain competitive in ASEAN member states. This paper ambitions to answer the query, what modified into the extent of the impact of compliance with full IFRS and IFRS for SMEs on profitability of agencies belong to real property enterprise? This paper moreover sought to decide whether there may be a sizeable distinction among the groups’ compliance with the overall PFRS and the PFRS for SMEs and to determine whether or now not there is a massive distinction among the companies’ financial normal overall performance earlier than and after the adoption of the PFRS for SMEs.Paired T-test have become employed in case you need to determine whether there is a big distinction between the agencies’ compliance with the entire PFRS and the PFRS for SMEs and to decide whether or not there may be a big difference some of the groups’ monetary performance earlier than and after the adoption of the PFRS for SMEs. Using STATA, the great appropriate version for every economic ratio on the subject of degree of compliance emerge as determined on. First, take a look at parm command became used to find out which most of the Least Squares Dummy Variable Regression Modes (LSDV1, LSDV2, LSDV3) underneath the Fixed Effects Model is the ideal version. Afterwards, Hausman Fixed Random Test changed into used to pick out out which is more suitable amongst Fixed Effects Model and Random Effects Model. If Fixed Effects Model modified into the more appropriate one, the Wald’s test turn out to be used to determine the best version among Fixed Effects Model and Ordinary Least Squares Model. On the alternative hand, if Random Effects Model became the more suitable one, the Breusch and Pagan Lagrangian Multiplier Test for Random Effect have become used to decide the satisfactory version amongst Random Effects Model and Ordinary Least Squares. Moreover, if Ordinary Least Squares became the splendid model, it is going to be in addition tested to check for heteroscedasticity and multicollinearity. White’s test became used to check for heterescedasticity and Variance Inflation Factor have become used to test if multicollinearity is gift. The results display that the adoption of PFRS for SMEs stepped forward the compliance of Philippine real property SMEs. However, no vast alternate became said inside the financial average performance of those companies (as measured with the resource of cross back on assets and go back on equity). This was further supported by the results of the panel regression. This means that despite having a relatively

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