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Chaudhary Charan Singh Haryana Agricultural University, Hisar

Chaudhary Charan Singh Haryana Agricultural University popularly known as HAU, is one of Asia's biggest agricultural universities, located at Hisar in the Indian state of Haryana. It is named after India's seventh Prime Minister, Chaudhary Charan Singh. It is a leader in agricultural research in India and contributed significantly to Green Revolution and White Revolution in India in the 1960s and 70s. It has a very large campus and has several research centres throughout the state. It won the Indian Council of Agricultural Research's Award for the Best Institute in 1997. HAU was initially a campus of Punjab Agricultural University, Ludhiana. After the formation of Haryana in 1966, it became an autonomous institution on February 2, 1970 through a Presidential Ordinance, later ratified as Haryana and Punjab Agricultural Universities Act, 1970, passed by the Lok Sabha on March 29, 1970. A. L. Fletcher, the first Vice-Chancellor of the university, was instrumental in its initial growth.

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2010 - 20153
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Subject: Statistics × End date: 2016 × Start date: 2010 × Type: Thesis × Thesis Type: Ph.D ×
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    ThesisItemOpen Access
    Probability Models for Spatial and Temporal Distributions of Rainfall in Haryana
    (CCSHAU, 2015) Bhushana Babu, V.; Hooda, B.K.
    The present investigation was carried to study probability models for spatial and temporal distributions of rainfall in Haryana. Various probability distributions describing daily, weekly and monthly rainfall behavior in Haryana were applied. The daily rainfall data of 34 years (1971 to 2005) were used covering 42 rainfall stations across Haryana. Exponential, gamma, Gumbel, lognormal and Weibull distributions were fitted to daily, weekly and monthly rainfall. Maximum Likelihood (ML) method was used for estimating parameters of the probability distributions. Kolmogorov-Smirnov (KS), Anderson-Darling (AD) and Chi-Square tests were used to test the goodness of fit of the fitted distributions. It was found that there is no single distribution that described the rainfall pattern of all the stations. However at most of the stations lognormal distribution was found to be best fit for daily rainfall based on KS and AD tests while Gumbel distribution was found to be best fit for weekly and monthly rainfall based on KS and Chi-Square tests. Multi-Criteria Decision Approach (MCDA) based on fuzzy majority approach was used for selection of best statistical distribution among Exponential, Gamma, Lognormal and Weibull distribution for describing daily, weekly and monthly rainfall. Lognormal distribution was found to be best fitting distribution to describe daily rainfall while gamma distribution was found to be best fitting distribution to describe weekly and monthly rainfall in various districts of Haryana.
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    ThesisItemOpen Access
    Prediction of milk production using penalized regression techniques in cattle
    (CCSHAU, 2013) Hemant Kumar; Hooda, B.K.
    Multiple linear regression models (MLR) have been widely used in dairy sciences to predict lifetime milk production in cattle on the basis of lactation traits. MLR often gives unsatisfactory results in the presences of high multicollinearity among the explanatory variables. Choice of functional form and selection of xplanatory variables is also important for getting a parsimonious and useful model for explaining any phenomenon. In the presence of multicollinearity and model mis-specification ordinary least square estimators of regression parameters generally have low bias and large variances resulting poor predictive performance. Keeping in view the presence of multicollinearity in mind shrinkage and penalized regression techniques have been used along with the artificial neural network for prediction of lifetime milk production on the basis of lactation traits. In the present study lactation traits such as previous lactation yield, age at first calving, lactation length, calving interval, service period, and dry period have been used for prediction of lifetime milk yield in crossbred cattle data. The lifetime milk production has been defined as total amount of milk produced by cattle from initiation of first lactation till the completion of third lactation. Small eigen values of correlation matrix of predictor variables, high value of variance inflation factor and higher condition index indicated presence of multicollinearity in crossbred cattle data. Consequently biased and penalized regression models have been adopted to take care of multicollinearity among the predictors. In addition to ridge regression the relatively recent techniques of penalized regression called LASSO and elastic net given by Tibshirani (1996) and Zou and Hastie (2005) respectively were also applied for developing prediction model for lifetime milk production and selection of principal lactation traits. On the basis of AIC and BIC values LASSO and elastic net outperformed the ridge regression and elastic net techniques was found most satisfactory. Forward selection, backward elimination, LASSO and elastic net were used for selection of best subset of lactation traits for prediction of lifetime milk production. It was observed that seven variables out of eleven were selected by LASSO and six by elastic net using optimal value of regularization parameters. The optimum value of regularization parameters was computed using 10- fold cross validation. The number of traits in best subset was found to six for backward elimination and four for forward selection method. On the basis of adjusted R2, AIC and BIC values and simplicity of the model it was concluded that subset selected by LASSO techniques having just two significant traits was best. Evaluation of predicting performance of multiple regression, ridge regression, LASSO, elastic net and ANNs models has been done by dividing the sample under study into two sets, by taking 90% observations in training set and 10% observations on test set. Coefficient of determination, root mean square error, mean absolute error, mean absolute percentage error and Theil’s U-statistics were computed for the test set, and based on these performance measures elastic net was found most satisfactory techniques for prediction of lifetime milk yield using lactation traits in crossbred cattle.
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    ThesisItemOpen Access
    Structural Equation Modeling With Latent Variables For Assessment Of Regional Development In Haryana
    (College Of Basic Sciences And Humanities Chaudhary Charan Singh haryana Agricultural University : Hisar, 2010) Sheoran,Parkash.Om.; Rai,Lajpat.