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Analyzing incomplete political science data: An alternative algorithm for multiple imputation

AMERICAN POLITICAL SCIENCE REVIEW 2001年第1期95卷 49-69页

作者： King, G Honaker, J Joseph, A Scheve, K Harvard Univ Ctr Basic Res Social Sci World Hlth Org Global Programme Evidence Hlth Policy Cambridge MA 02138 USA Harvard Univ Ctr Basic Res Social Sci Dept Govt Cambridge MA 02138 USA Yale Univ Inst Social & Policy Studies Dept Polit Sci New Haven CT 06520 USA

We propose a remedy for the discrepancy between the way political scientists analyze data with missing values and the recommendations of the statistics community. Methodologists and statisticians agree that "multiple imputation" is a superior approach to the problem of missing data scattered through one's explanatory and dependent variables than the methods currently used in applied data analysis. The discrepancy occurs because the computational algorithms used to apply the best multiple imputation models have been slow, difficult to implement, impossible to run with existing commercial statistical packages, and have demanded considerable expertise. We adapt an algorithm and use it to implement a general-purpose, multiple imputation model for missing data. This algorithm is considerably faster and easier to use than the leading method recommended in the statistics literature. We also quantify the risks of current missing data practices, illustrate how to use the new procedure, and evaluate this alternative through simulated data as well as actual empirical examples. Finally, we offer easy-to-use software that implements all methods discussed.

关键词： .Analyzing algorithms missing data cult American Political Science incomplete missing values multiple imputation Center for Basic alternative algorithm Data An alternative imputation model

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Development of an alternative algorithm for a class of H-infinity design problems

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OPTIMAL CONTROL APPLICATIONS & METHODS 1997年第2期18卷 149-158页

作者： Yang, TC School of Engineering University of Sussex Brighton BN1 9QT United Kingdom

This article presents a tutorial exposition of an algorithm suggested by Kwakernaak which is an alternative to the standard state space solution for a class of H-infinity, optimization problems. In addition, a set of formulae for the computation required is derived. From these formulae one can simply use an ordinary computer language to write a programme for the design purpose and therefore avoid an expensive expenditure on some software packages. A modification of a weighting function is also suggested. (C) 1997 by John Wiley & Sons, Ltd.

关键词： H-infinity control mixed sensitivity design alternative algorithm

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FURTHER DEVELOPMENT OF AN alternative algorithm FOR A CLASS OFH∞DESIGN PROBLEMS

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Optimal Control Applications and Methods 1998年第2期18卷

作者： T. C. YANG School of Engineering University of Sussex Brighton BN1 9QT U.K.

This article presents a tutorial exposition of an algorithm suggested by Kwakernaak which is an alternative to the standard state space solution for a class of H ∞ optimization problems. In addition, a set of formulae for the computation required is derived. From these formulae one can simply use an ordinary computer language to write a programme for the design purpose and therefore avoid an expensive expenditure on some software packages. A modification of a weighting function is also suggested. © 1997 John Wiley & Sons, Ltd.

关键词： H∞ control mixed sensitivity design alternative algorithm

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Load spectra growth modelling and extrapolation with REBMIX

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STRUCTURAL ENGINEERING AND MECHANICS 2009年第5期33卷 589-604页

作者： Volk, Matej Fajdiga, Matija Nagode, Marko Univ Ljubljana Fac Mech Engn SI-1000 Ljubljana Slovenia

In the field of predicting structural safety and reliability the operating conditions play an essential role. Since the time and cost limitations are a significant factors in engineering it is important to predict the future operating conditions as close to the actual state as possible from small amount of available data. Because of the randomness of the environment the shape of measured load spectra can vary considerably and therefore simple distribution functions are frequently not sufficient for their modelling. Thus mixed distribution functions have to be used. In general their major weakness is the complicated calculation of unknown parameters. The scope of the paper is to investigate the load spectra growth for actual operating conditions and to investigate the modelling and extrapolation of load spectra with algorithm for mixed distribution estimation, REBMIX The data obtained from the measurements of wheel forces and the braking moment on proving ground is used to generate load spectra.

关键词： load spectra growth extrapolation reliability mixed distribution function alternative algorithm

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Variation of fluorescence intensity in Pleistocene pollen and the correlation of fluvial deposits in the Khorat Plateau, Thailand

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PALYNOLOGY 2018年第1期42卷 28-35页

作者： Yang, Feng-Chun Grote, Paul J. Honghe Univ Coll Life Sci & Technol Mengzi Yunnan Peoples R China Suranaree Univ Technol Inst Sci Sch Biol Nakhon Ratchasima 30000 Thailand Nakhon Ratchasima Rajabhat Univ Northeastern Res Inst Petrified Wood & Mineral Re Nakhon Ratchasima 30000 Thailand

Fluorescence analysis of modern pollen grains is a well-established technique, but its use on fossil material is significantly less prevalent. A study focused on pollen and spore fluorescence and its indication was carried out using samples collected from a 14-m-deep exposed section at an abandoned fluvial terrace in the Khorat Plateau, the center of the Indochina peninsula. Fluorescent signals were well preserved in the deposits at various depths. Thirty-seven fluorescent pollen and spore taxa were discovered in six layers dated from Middle to Late Pleistocene. An alternative algorithm method was used to calculate the fluorescence intensity (FI) in the layers. The FI of each fossil pollen taxon, represented by an assigned value, is different among the layers throughout the section. Differences in the FI indicate varied preservation conditions. General linear analysis indicates that the total FI value is related to the pollen taxa but not to the deposit depth.

关键词： Quaternary pollen fluorescence alternative algorithm fluvial

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A search space optimization technique for improving ambiguity resolution and computational efficiency

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EARTH PLANETS AND SPACE 2000年第10期52卷 807-812页

作者： Kim, D Langley, RB Univ New Brunswick Dept Geodesy & Geomat Engn Geodet Res Lab Fredericton NB Canada

An Optimal Method for Estimating GPS Ambiguities (OMEGA) that enables very high performance and computational efficiency has been developed and demonstrated. This method employs two search space reduction processes-a scaling and a screening process-that are related to the search space transformation and the ambiguity candidate filtering in multi-search levels. To obtain the highest efficiency, an optimization procedure, which determines the parameters to minimize the number of candidates under given conditions, is implemented in closed form before the search-verification step. The method is essentially based on the least-squares approach originally proposed by Hatch but uses a modified and more efficient process. Two improved algorithms are introduced in this paper. First, an alternative algorithm for the spectral decomposition, which reduces the dimension of the residuals vector to its degrees of freedom, is given in closed form. This algorithm is implemented in the computational step of the quadratic form of the residuals in order to increase computational efficiency. Second, an efficient error model for the threshold of the filter equation that is used to derive the search space scaling process is given. This error model shows two advantages: 1) it bounds noise signals of the filter equation;2) it gives efficient thresholds so that the scaling effects for the search space can be increased.

关键词： .residuals search space ambiguity error model alternative algorithm spectral decomposition quadratic form filter equation

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Right-hand-side updating for fast computing of genomic breeding values

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GENETICS SELECTION EVOLUTION 2014年第1期46卷 1-11页

作者： Calus, Mario P. L. Wageningen UR Livestock Res Anim Breeding & Genom Ctr NL-6700 AC Wageningen Netherlands

Background: Since both the number of SNPs (single nucleotide polymorphisms) used in genomic prediction and the number of individuals used in training datasets are rapidly increasing, there is an increasing need to improve the efficiency of genomic prediction models in terms of computing time and memory (RAM) required. Methods: In this paper, two alternative algorithms for genomic prediction are presented that replace the originally suggested residual updating algorithm, without affecting the estimates. The first alternative algorithm continues to use residual updating, but takes advantage of the characteristic that the predictor variables in the model (i.e. the SNP genotypes) take only three different values, and is therefore termed "improved residual updating". The second alternative algorithm, here termed "right-hand-side updating" (RHS-updating), extends the idea of improved residual updating across multiple SNPs. The alternative algorithms can be implemented for a range of different genomic predictions models, including random regression BLUP (best linear unbiased prediction) and most Bayesian genomic prediction models. To test the required computing time and RAM, both alternative algorithms were implemented in a Bayesian stochastic search variable selection model. Results: Compared to the original algorithm, the improved residual updating algorithm reduced CPU time by 35.3 to 43.3%, without changing memory requirements. The RHS-updating algorithm reduced CPU time by 74.5 to 93.0% and memory requirements by 13.1 to 66.4% compared to the original algorithm. Conclusions: The presented RHS-updating algorithm provides an interesting alternative to reduce both computing time and memory requirements for a range of genomic prediction models.

关键词： Markov Chain Monte Carlo Genomic Prediction Group Code alternative algorithm Allele Substitution Effect

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Linear Twin SVM for Learning from Label Proportions

Linear Twin SVM for Learning from Label Proportions

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IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Wang, Bo Chen, Zhensong Qi, Zhiquan Chinese Acad Sci Res Ctr Fictitious Econ & Data Sci Beijing 100190 Peoples R China Chinese Acad Sci Key Res Lab Big Data Min & Knowledge Management Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Management Beijing 100190 Peoples R China

ISBN: (纸本)9781467396189

In this paper, we study the problem of learning from label proportions in which label information of data is provided in bag level. In this kind of problem, training data is grouped into various bags and only the proportions of positive instances is known. Inspired by proportion-SVM, we propose a new classification model based on twin SVM, which is also in a large-margin framework and only needs to solve two smaller problems. Avoiding making restrictive assumptions of the data, our model can learn the labels of every single instance based on group proportions information. In order to solve the non-convex problem in our new model, we propose an alternative algorithm to obtain the optimal solution efficiently. Also, we prove the effectiveness of our method in theoretical and experimental way.

关键词： Learning from label proportions Twin SVM alternative algorithm Large-margin

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Improving Energy Efficiency of Massive MIMO Relay Systems using Power Bisection Allocation for Cell-Edge Users 27

Improving Energy Efficiency of Massive MIMO Relay Systems us...

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27th Iranian Conference on Electrical Engineering (ICEE)

作者： Koolivand, Mohammad Bahonar, Mohammad Hossein Fazel, Mohammad Sadegh Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran

ISBN: (纸本)9781728115085

This paper studies downlink energy efficiency (EE) of a cellular massive Multiple Input Multiple Output (MIMO) system with massive number of antennas at both base station (BS) and relay considering cell-edge users which is less investigated in the literature. Some improving methods for base station (BS) and relay power allocation under quality of service constraints are proposed. The EE optimization problem is provided over BS and relay power variables (power dimensions). Considering the quasi-concavity property of the EE function relative to each power variable, we propose to use a power bisection algorithm (PBA) in one dimension, followed by the exhaustive search in the other dimension (ODS algorithm) which is called PB-ODS algorithm and also a method to limit the range of power variables. The results show that the performance of the PB-ODS algorithm approaches the performance of optimal solution which is exhaustive search in both dimensions while it has a lower complexity. In addition to that we suggest to use the PBA in two dimensions alternatively as the sub-optimal alternative optimization (AOP) algorithm. The complexity can highly be reduced using the AOP algorithm with a slight but acceptable degradation in performance which makes the algorithm much suitable for practical use.

关键词： Energy efficiency bisection algorithm massive MIMO relay system alternative algorithm quasi-concave function

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OSAT: a tool for sample-to-batch allocations in genomics experiments

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BMC GENOMICS 2012年第1期13卷 689-689页

作者： Yan, Li Ma, Changxing Wang, Dan Hu, Qiang Qin, Maochun Conroy, Jeffrey M. Sucheston, Lara E. Ambrosone, Christine B. Johnson, Candace S. Wang, Jianmin Liu, Song Roswell Pk Canc Inst Dept Biostat & Bioinformat Buffalo NY 14263 USA SUNY Buffalo Dept Biostat Buffalo NY 14214 USA Roswell Pk Canc Inst Buffalo NY 14263 USA

Background: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. Results: We describe OSAT (Optimal Sample Assignment Tool), a bioconductor package designed for automated sample-to-batch allocations in genomics experiments. Conclusions: OSAT is developed to facilitate the allocation of collected samples to different batches in genomics study. Through optimizing the even distribution of samples in groups of biological interest into different batches, it can reduce the confounding or correlation between batches and the biological variables of interest. It can also optimize the homogeneous distribution of confounding factors across batches. It can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideally balanced designs.

关键词： Genomic Study Optimization Step Batch Effect Randomized Complete Block Design alternative algorithm

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