In this paper, classes of separate and combined regression-cum-ratio estimators have been proposed for estimating the finite population mean in stratified random sampling. The expressions for biases and mean square errors (MSEs) of the proposed classes have been derived to the first order of approximation. It has also been verified that the proposed classes of estimators, at their optimum conditions, are equivalent to the separate regression estimator. The proposed classes of estimators have been compared with the other existing estimators using MSE criterion, and the conditions under which the proposed classes perform better have been obtained. Numerical illustrations are given in support of theoretical findings. Relevance of the work The estimation theory is relevant to various interdisciplinary areas of research including economics, clinical trials, population studies, engineering, agriculture, etc. Also, the problem of estimation of mean is of huge importance in research, for instance, the estimation of: average agricultural production, average life span of persons in a region, mean concentration of dissolved minerals in water, and much more. For the estimation of mean, several design-based approaches are being widely used, for instance, simple random sampling, stratified random sampling, two-phase sampling, etc. If the population under study is homogeneous, then the simple random sampling design is used at the estimation stage. However, in various practical situations, the research study is based on the heterogeneous population, and in that case the stratified random sampling procedure is preferable over the simple random sampling. Considering the above fact, an attempt has been made in this paper to develop the classes of generalized estimators for the mean of the variable under study using stratified random sampling.

在本文中，为了对分层随机抽样中的有限总体均值进行估计，提出了单独的和组合的回归与比率估计值的组合。拟议类别的偏差和均方误差（MSE）的表达式已推导至近似的一阶。还已经证明，在最佳条件下，建议的估算器类别与单独的回归估算器等效。使用MSE准则，将拟议的估计量类别与其他现有的估计量进行了比较，并获得了拟议的类别表现更好的条件。给出了数字说明以支持理论发现。工作的相关性估计理论与跨学科研究领域相关，包括经济学，临床试验，人口研究，工程学，农业等。此外，均值估计问题在研究中非常重要，例如：生产，一个地区人的平均寿命，水中溶解矿物质的平均浓度等等。为了估计均值，广泛使用了几种基于设计的方法，例如简单随机抽样，分层随机抽样，两阶段抽样等。如果所研究的总体是同质的，则使用简单随机抽样设计在估算阶段。但是，在各种实际情况下，本研究都是基于异质种群，在这种情况下，分层随机抽样程序比简单随机抽样更为可取。考虑到上述事实，本文已尝试使用分层随机抽样为研究中的变量的均值开发广义估计量的类别。