While the direct method allocates support department costs only to the producing departments, the sequential method and the reciprocal method allocate support service costs among some (or all) interacting support departments before allocating costs to the producing departments.
The sequential method is used to allocate the cost of service departments to other departments within an organization. Under this approach, the cost of each service department is allocated one department at a time.
Sequential methods build and utilize statistical models in which the sample size or the duration of the observation period is itself part of the random observable. Madhu Mazumdar, Heejung Bang, in Essential Statistical Methods for Medical Statistics, 2011
The costs allocated from a support department are its direct costs plus any costs it receives in allocations from other support departments. 2. Sequential allocation may be more accurate than the direct method because it recognizes some interactions among the support departments.
The sequential method is used to allocate the cost of service departments to other departments, where the cost of each service department is allocated one department at a time.
International Journal of Quantitative and Qualitative Research Methods Vol.5, No.2, pp.10-27, May 2017
The Sequential model. Author: fchollet Date created: 2020/04/12 Last modified: 2020/04/12 Description: Complete guide to the Sequential model. View in Colab • GitHub source
x: It is tf.Tensor that contains all the input data. y: It is tf.Tensor that contains all the output data. args: It is object type, it’s variables are follows: batchSize: It define the number of samples that will propagate through training. epochs: It define iteration over the training data arrays. verbose: It help in showing the progress for each epoch.
Sequential methods build and utilize statistical models in which the sample size or the duration of the observation period is itself part of the random observable.
We use a sequential method to allocate software test cases among partitions of a software to minimize the expected loss incurred by the Bayes estimator of the overall software reliability. The Bayesian approach allows us to take advantage of the previous information obtained from testing. We will show that the myopic sampling scheme has advantages over the optimal fixed in terms of the expected loss incurred when the overall reliability is estimated by its Bayes estimator. Theoretical results and numerical are provided for the comparison. This myopic scheme shows a great promise in software reliability estimation.
The sequential methodology previously described was followed for kinetic constants estimation in order to decrease the number of parameters estimated simultaneously and to avoid convergence problems.
Social sequence analysis refers to a set of methods, suitable for the analysis of sequences of events or activities or other phenomena pertaining to problems from social sciences; the interested reader may refer to Abbott (1995), Elzinga and Studer (2015), or the book by Cornwell (2015), and the edited volume by Ritschard and Studer (2018). Although literature review indicates that it is only during the last four decades that the sequential methods have become popular in the field of social sciences, it appears that there is an increasing interest in such methods recently; this can be readily seen from the books of Cornwell (2015), and Ritschard and Studer (2018). This could perhaps be attributed to the current great availability of longitudinal data sources or real-time social data, and by the readily available software packages for performing the respective analysis. Nowadays, sequential analysis plays a key role, among others, in the study of life course, occupational careers and health successive conditions (trajectories). One of the extensively studied problems under social sequence analysis is the computation of pairwise dissimilarities (distances) between sequences and subsequent use of these distances for creating clusters. For example, the most frequently used distance between sequences is the optimal matching metric; it expresses the cost of making the two sequences exactly the same based on three operations: replacement, deletion, and insertion.
In order to apply the proposed sequential method for kinetic parameter estimation in the FCC process three feeds were used for MAT experiments: GO-1, a typical FCC feedstock, GO-2, Heavy Vacuum Gas Oil and, GO-3, the typical FCC feedstock plus 5 vol% atmospheric residuum. Characterization of theses feeds were presented in a previous work [5].
It can be observed from these figures that the application of the proposed sequential method to estimate the rate constants of the 5-lump kinetic model predicts sufficiently well the experimental data with average deviations less than 2% .
As its main application was the quality control of manufactured materials, its publication was only authorized after the end of the war, in 1947. Another class of sequential test is based on triangular continuation regions ( Anderson, 1960 ). The basic idea on which these methods rely is to constantly use the available information to determine whether the data are compatible with null hypothesis, with alternative hypothesis, or insufficient to choose between these two hypotheses. In the first two cases, the trial is stopped and the conclusion is obtained whereas in the third case the trial continues. The trial is further processed until the data allows a legitimate (or per-protocol) decision between the two hypotheses. An example of a completely sequential trial can be found in Jones et al. (1982 ).
Sequential methods build and utilize statistical models in which the sample size or the duration of the observation period is itself part of the random observable.
We use a sequential method to allocate software test cases among partitions of a software to minimize the expected loss incurred by the Bayes estimator of the overall software reliability. The Bayesian approach allows us to take advantage of the previous information obtained from testing. We will show that the myopic sampling scheme has advantages over the optimal fixed in terms of the expected loss incurred when the overall reliability is estimated by its Bayes estimator. Theoretical results and numerical are provided for the comparison. This myopic scheme shows a great promise in software reliability estimation.
The sequential methodology previously described was followed for kinetic constants estimation in order to decrease the number of parameters estimated simultaneously and to avoid convergence problems.
Social sequence analysis refers to a set of methods, suitable for the analysis of sequences of events or activities or other phenomena pertaining to problems from social sciences; the interested reader may refer to Abbott (1995), Elzinga and Studer (2015), or the book by Cornwell (2015), and the edited volume by Ritschard and Studer (2018). Although literature review indicates that it is only during the last four decades that the sequential methods have become popular in the field of social sciences, it appears that there is an increasing interest in such methods recently; this can be readily seen from the books of Cornwell (2015), and Ritschard and Studer (2018). This could perhaps be attributed to the current great availability of longitudinal data sources or real-time social data, and by the readily available software packages for performing the respective analysis. Nowadays, sequential analysis plays a key role, among others, in the study of life course, occupational careers and health successive conditions (trajectories). One of the extensively studied problems under social sequence analysis is the computation of pairwise dissimilarities (distances) between sequences and subsequent use of these distances for creating clusters. For example, the most frequently used distance between sequences is the optimal matching metric; it expresses the cost of making the two sequences exactly the same based on three operations: replacement, deletion, and insertion.
In order to apply the proposed sequential method for kinetic parameter estimation in the FCC process three feeds were used for MAT experiments: GO-1, a typical FCC feedstock, GO-2, Heavy Vacuum Gas Oil and, GO-3, the typical FCC feedstock plus 5 vol% atmospheric residuum. Characterization of theses feeds were presented in a previous work [5].
It can be observed from these figures that the application of the proposed sequential method to estimate the rate constants of the 5-lump kinetic model predicts sufficiently well the experimental data with average deviations less than 2% .
As its main application was the quality control of manufactured materials, its publication was only authorized after the end of the war, in 1947. Another class of sequential test is based on triangular continuation regions ( Anderson, 1960 ). The basic idea on which these methods rely is to constantly use the available information to determine whether the data are compatible with null hypothesis, with alternative hypothesis, or insufficient to choose between these two hypotheses. In the first two cases, the trial is stopped and the conclusion is obtained whereas in the third case the trial continues. The trial is further processed until the data allows a legitimate (or per-protocol) decision between the two hypotheses. An example of a completely sequential trial can be found in Jones et al. (1982 ).