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Full-Model Regression Sum of Squares of Randomized Complete Block Design Having One Unrecorded Observation

机译:随机性完整块设计的全模型回归总和具有一个未记录的观察

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In the classical design of experiment, a randomized complete block design (RCBD) is a helpful experimental design because this design uses a small number of experimental units. The randomized c?mplete block design is comprised of two factors, i.e., a nuisance factor and a potential factor. In many real experiments, some data might be missing or unrecorded. The instant formulae were not provided for an analysis of variance in this case. This paper took into account the randomized complete block design (RCBD) with a treatments and b blocks. In this contribution, the RCBD with an unrecorded value was analyzed by means of the exact scheme with the model comparison approach. The advantages of the exact scheme are that the unrecorded value for the unfilled cell is not estimated and the treatment sum of squares is unbiased. It is important to note that there is no ready-made formula for RCBD in the past. Hence, this research paper provided the mathematical formulae for the fitted parameters and the overall regression sum of squares (ORSS) for the full model of experimental data. It is also noted that the ORSS is imperative for the analysis of the variance by means of the exact scheme.
机译:在经典的实验设计中,随机完整的块设计(RCBD)是一种有用的实验设计,因为这种设计使用了少量的实验单元。随机C?Mplete块设计由两个因素,即滋扰因子和潜在因子组成。在许多真实实验中,一些数据可能丢失或未记录。在这种情况下,未提供瞬间公式以分析方差。本文考虑了随机的完整块设计(RCBD),具有治疗和B块。在此贡献中,通过使用模型比较方法的确切方案分析具有未记录值的RCBD。确切方案的优点是未估计未填充小区的未记录值,并且方块的处理总和是无偏见的。值得注意的是,过去没有RCBD的现成公式。因此,本研究论文提供了用于拟合参数的数学公式和用于完整模型的实验数据的方块(ORSS)的总体回归和。还应注意到,通过确切的方案对差异进行分析。

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