Residual effect of crop residues along with green manure, microbial culture and inorganic fertilizer on yield and soil properties of wheat grown after rice were studied. The following treatments such as control, straw burn (5 t ha -1 ) , straw incorporation (5 t ha -1 ), straw (5 t ha -1 ) + 25% N of recommended dose , straw (5 t ha -1 ) + green manure (5 t ha -1 ) and straw (5 t ha -1 ) + microbial culture (a cocktail of Aspergillus, Trichoderma, Pleurotus and Phanerochaete) were imposed on rice and their residual effects on the yield of wheat and nutrients content in soils were evaluated. Results showed that application of straw (5 t ha -1 ) + green manure (5 t ha -1 ) recorded the highest yield of wheat followed by the straw (5 t ha -1 ) + 25%N of recommended dose > straw (5 t ha -1 ) + microbial culture > straw incorporation (5 t ha -1 ) > straw burn (5 t ha -1 ) > control. Availability of soil nutrients particularly N, P, K and organic carbon also increased following the above trend.
The paper deals with the estimation of survival function of a particular random variable of interest in proportional hazard model of random censorship under the condition that data are randomly censored by k independent variables. Estimators are constructed using results from Abdushukurov (1984), Cheng and Lin (1984), Ebrahimi (1985) and Kaplan and Meier (1958). The asymptotic behaviour of all these estimators is investigated. Numerical results are provided to calculate the efficiencies of ACL and Ebrahimi's estimators in comparsion to classical Kaplan-Meier (1958) estimator.
In many practical situations dealing with parallel systems, the failure times of the components are not observable unless that is the last one resulting in the failure of the system. Based on observation on the life time of the system, nonparametric estimation of the life time distributions of the components is considered. Dealing with a parallel system with two components, a competing risks framework is developed and an algorithm of the EM type for maximum likelihood estimation is obtained. The method is illustrated with a simulated data set.
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