The description and analysis of wool growth

1977 ◽  
Vol 28 (4) ◽  
pp. 737 ◽  
Author(s):  
BN Nagorcka
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Linear Regression ◽  
Least Squares ◽  
Ordinary Least Squares ◽  
Time Dependent ◽  
Recursive Least Squares ◽  
Growth Time ◽  
Body Weight Change ◽  
Wool Growth

Analyses of experimental estimates of the wool growth rate as a function of intake have previously been based on time-independent equations and linear regression with ordinary least squares. Some of these results are reanalysed with the assumption that the sheep is a dynamic system; hence a time-dependent description of wool growth is proposed. A recursive least squares technique has been used, and the results demonstrate that there is a 3½ week lag between intake and wool growth. Time-independent descriptions have not taken account of this and have led to the misconception that efficiency is a function of body weight change.

scholarly journals The Relation Between the Responses of Wool Growth and Body Weight to Changes in Feed Intake

1962 ◽  
Vol 15 (4) ◽  
pp. 720 ◽  
Author(s):  
KA Ferguson
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Feed Intake ◽  
Weight Change ◽  
Productive Efficiency ◽  
Intake Rate ◽  
Body Weight Change ◽  
Growth Responses ◽  
Wool Growth

The wool growth responses to changes in feed intake are related to the changes produced in body weight. The relation is expressed by the equation W = Ei-kG, where W = wool growth rate, i = feed intake rate, G = rate of body weight change, and E and k are constants. The ratio of E to k in sheep of different productive efficiency was found to be constant.

scholarly journals Tolerance Intervals in a Heteroscedastic Linear Regression Context with Applications to Aerospace Equipment Surveillance

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Janet Myhre ◽  
Daniel R. Jeske ◽  
Michael Rennie ◽  
Yingtao Bi
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Performance Metrics ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Automated System ◽  
Least Squares Regression ◽  
Data Set ◽  
Tolerance Intervals ◽  
Power Of The Test

A heteroscedastic linear regression model is developed from plausible assumptions that describe the time evolution of performance metrics for equipment. The inherited motivation for the related weighted least squares analysis of the model is an essential and attractive selling point to engineers with interest in equipment surveillance methodologies. A simple test for the significance of the heteroscedasticity suggested by a data set is derived and a simulation study is used to evaluate the power of the test and compare it with several other applicable tests that were designed under different contexts. Tolerance intervals within the context of the model are derived, thus generalizing well-known tolerance intervals for ordinary least squares regression. Use of the model and its associated analyses is illustrated with an aerospace application where hundreds of electronic components are continuously monitored by an automated system that flags components that are suspected of unusual degradation patterns.

Robust Weighted Least Squares Estimation of Regression Parameter in the Presence of Outliers and Heteroscedastic Errors

2014 ◽  
Vol 71 (1) ◽  
Author(s):  
Bello Abdulkadir Rasheed ◽  
Robiah Adnan ◽  
Seyed Ehsan Saffari ◽  
Kafi Dano Pati
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Robust Regression ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Model Parameters ◽  
Constant Variance ◽  
Regression Parameters ◽  
M Estimation

In a linear regression model, the ordinary least squares (OLS) method is considered the best method to estimate the regression parameters if the assumptions are met. However, if the data does not satisfy the underlying assumptions, the results will be misleading. The violation for the assumption of constant variance in the least squares regression is caused by the presence of outliers and heteroscedasticity in the data. This assumption of constant variance (homoscedasticity) is very important in linear regression in which the least squares estimators enjoy the property of minimum variance. Therefor e robust regression method is required to handle the problem of outlier in the data. However, this research will use the weighted least square techniques to estimate the parameter of regression coefficients when the assumption of error variance is violated in the data. Estimation of WLS is the same as carrying out the OLS in a transformed variables procedure. The WLS can easily be affected by outliers. To remedy this, We have suggested a strong technique for the estimation of regression parameters in the existence of heteroscedasticity and outliers. Here we apply the robust regression of M-estimation using iterative reweighted least squares (IRWLS) of Huber and Tukey Bisquare function and resistance regression estimator of least trimmed squares to estimating the model parameters of state-wide crime of united states in 1993. The outcomes from the study indicate the estimators obtained from the M-estimation techniques and the least trimmed method are more effective compared with those obtained from the OLS.

Heritability Estimates for Juvenile Body weight by Least Squares and DFREML in a Commercial Broiler Breeder Dam Population

1994 ◽  
Vol 1994 ◽  
pp. 51-51
Author(s):  
A.J. Morris ◽  
G.E. Pollott
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Least Squares ◽  
Production Efficiency ◽  
Early Growth ◽  
Broiler Breeder ◽  
Derivative Free ◽  
Commercial Broiler ◽  
Body Weight Measure ◽  
Different Sources

To date commercial broiler breeders have focused primarily on increasing early growth rate in selection programmes aimed at improving overall production efficiency. In commercial programmes, early growth rate is simplified to a single body weight measure taken at a fixed age during the growth phase approaching common slaughter weights. Most recent selection studies report heritabilities from experimental populations that are at best, synthesised from crossing modern broiler material from several different sources (Leenstra et al, 1986; Wang et al, 1991). Therefore, such populations are likely to exhibit greater heterozygosity than many commercial lines which have undergone many generations of intense selection in closed populations. This paper reports heritabilities estimated using both least squares and derivative-free maximum likelihood techniques for data from a commercial breeder dam line which has remained closed since its inception in 1975.

Correlations between energy consumption per capita, growth rate, industrialisation, trade volume and urbanisation: the case of Turkey

2018 ◽  
Vol 4 (10) ◽  
pp. 118-127
Author(s):  
Funda Yurdakul
Keyword(s):  
Growth Rate ◽  
Energy Consumption ◽  
Least Squares ◽  
Ordinary Least Squares ◽  
Trade Volume ◽  
Long Run ◽  
Turkish Economy ◽  
Equilibrium Relationship ◽  
Per Capita ◽  
Relationship Of

This study examines the relationship of energy consumption per capita with growth rate, industrialisation, trade volume and urbanisation in Turkish economy throughout the 1980–2015 period using the Engle-Granger, Fully modified ordinary least squares (FMOLS), canonical cointegration regression (CCR) and dynamic ordinary least squares (DOLS) methods. Analysis results revealed a long-run equilibrium relationship between the change in energy consumption per capita and growth rate, industrialisation, trade volume and urbanisation. Urbanisation, industrialisation, growth rate and trade volume positively influence the change in energy consumption per capita. Keywords: Energy consumption, Engle-Granger method, fully modified ordinary least squares (FMOLS) method, canonical cointegration regression (CCR), dynamic ordinary least squares (DOLS) method.

scholarly journals The Growth and Composition of Wool V. Stimulation of Wool Growth by the Abomasal Administration of Varying Amounts of Casein

1969 ◽  
Vol 22 (3) ◽  
pp. 745 ◽  
Author(s):  
PJ Reis
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Sulphur Content ◽  
Wool Growth ◽  
Stimulation Of

In a series of five experiments, varying amounts of casein (60~200 gjday) were given to sheep, in the diet or via the abomasum, as supplements to various diets at several levels of intake (400~1200 gjday). Effects on growth rate and sulphur content of wool and on body weight were investigated.

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