Ridge regression estimator for milk production in cattle

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dc.contributor.advisorGrover, Deepak
dc.contributor.authorSharma, Yogesh
dc.date.accessioned2016-11-21T14:27:17Z
dc.date.available2016-11-21T14:27:17Z
dc.date.issued2006
dc.description.abstractThe prediction of life time production of an animal on farm may be helpful to decide, whether particular animal should cull or not on the basis of performance of first lactation only. The present investigation has been conducted to find out an appropriate estimation procedure to estimate the regression coefficients of life time production multiple linear regression model of Hariana breed of cattle. To find out an appropriate estimation procedure, life time production multiple linear regression model of Hariana breed of cattle has been studied in detail. Normal probability plot and histogram used to check the normality assumption of model. Plots of standardized residuals against each regressor were utilized to detect the outlier cases in this study. Presence of influential observations was detected with the help of three different measures. Each influential observation and their different combinations excluded from the model one by one to check the considerable change in mean square error value, coefficient of determination value, in sign and significance of regression coefficients. Presence of multicollinearity in independent variables was diagnosed with the help of examination of correlation matrix, variance inflation factors, eigenvalues inspection and condition indices. The result revealed that problem of multicollinearity was serious in the study. In this investigation two estimation procedures, i.e., ordinary least squares and ridge regression technique were compared. Criterion of mean square error, sign and significance of regression coefficients were used to compare the performance of each estimator. The value of ridge constant (K)was estimated by three different methods and accordingly the optimum value of ridge constant (K) was found. The ridge regression estimator by using optimum value of ridge constant was found better as compared to ordinary least squares estimator in terms of mean square error criterion.en_US
dc.identifier.urihttp://krishikosh.egranth.ac.in/handle/1/86680
dc.language.isoenen_US
dc.publisherCCSHAUen_US
dc.subStatistics
dc.subjectRidge regression, Ordinary least squares, Outliers, Influential Observations, Normal probability plot, Histogram, Multicollinearity.en_US
dc.these.typeM.Sc
dc.titleRidge regression estimator for milk production in cattleen_US
dc.typeThesisen_US
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