产量数据误差的识别与过滤方法研究

针对产量数据包含大量误差的问题,首先研究分析产量数据的获取过程,从统计分析的角度,将可能造成产量数据误差的归纳为系统误差、随机误差和粗大误差。然后分别针对不同产量数据的误差来源,提出误差数据处理方法,设计并实现6种过滤器:割台状态、填充和排空延时、传感器数据异常、不切实际的产量值、局部空间的异常值、短收割段和坐标重叠。最后仿真实验表明,过滤后产量数据由随机因素引起的产量数据空间变异得到显著改善。

New Class of Almost Unbiased Modified Ratio Cum Product Estimators with Knownparameters of Auxiliary Variables

This manuscript deals with new class of almost unbiased ratio cum product estimators for the estimation of population mean of the study variable by using the known values auxiliary variable. The bias and mean squared error of proposed estimators are obtained. An empirical study is carried out to assess the efficiency of proposed estimators over the existing estimators with the help of some known natural populations and it shows that the proposed estimators are almost unbiased and it perform better than the existing estimators.