共查询到19条相似文献，搜索用时 187 毫秒
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本文把一般的回归分析中观测变量有测量误差的问题引入到面板数据模型中,考虑有测量误差的动态面板数据模型,推导出模型中参数满足的各种矩条件,利用广义矩估计的方法得到了模型中参数的一致估计。并且给出了模型错误识别时参数的一个估计值。最后,对于不同的测量误差结构,通过Monte Carlo试验验证了我们给出三种估计的优良性。 相似文献
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在部分线性变系数面板数据模型基础上,引入了不可观测的固定效应,研究了模型的估计问题.首先引入虚拟变量消除固定效应带来的影响,然后应用轮廓最小二乘估计法对模型中的参数进行估计,接着对模型中的变系数基于B样条基函数展开的方法逼近,再对模型中的未知系数函数进行估计,最后通过Monte Carlo模拟方法验证了当解释变量取自于... 相似文献
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基于二项分布B(n,p)总体,给出了未知参数p2的矩估计和极大似然估计,并讨论了估计量的无偏性。 相似文献
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本文讨论了三参数Weibull分布的参数估计问题 ,分别给出了参数的矩法估计和最大似然法估计。某些气候要素极值如风速极值的渐近分布以很高的拟合精度遵循三参数Weibull分布。 相似文献
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本讨论了三参数Weibull分布的参数估计问题，分别给出了参数的矩法估计和最大似然法估计。某些气候要素极值如风速极值的渐近分布以很高的拟合精度遵循三参数Weibull分布。 相似文献
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郭化文 《岱宗学刊(泰安教育学院学报)》2000,(3):10-13
本讨论了三参数Weibull分布的参数估计问题，分别给出：参数的矩法估计和极大拟然法估计，某些气候要素极值如风速极值的渐近分布以提高的拟合精度遵循三参数Weibull分布。 相似文献
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本文简要地叙述了矩估计的思想方法、完整的求解过程,并在此基础上给出矩估计的计算步骤和实践应用.同时,也指出了矩估计的一些缺点. 相似文献
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把高斯混合模型(GMM)用于视频流的错误隐藏技术中,并对此进行了分析、论证、研究。GMM依据邻近的时域和空域的信息,用最小均方差来估计丢失像素的区域;如部分视频数据丢失,根据丢失视频数据邻近的时-空域信息通过GMM做一个最小均方差估计;如丢失宏块周围的时域信息也随之丢失,则采用反复迭代估计的方法来解决。和现有的基于时-空域的错误隐藏方法相比,基于GMM的错误隐藏方法提高了PSNR,且对于大范围内的丢包率都是有效的。仿真实验也证实了基于GMM的错误隐藏方法能较好地提高和改善视频的主客观质量。 相似文献
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《Structural equation modeling》2013,20(2):174-205
This research was designed to investigate how much more suitable moving average (MA) and autoregressive-moving average (ARMA) models are for longitudinal panel data in which measurement errors correlate than AR, quasi-simplex, and 1-factor models. The conclusions include (a) when testing for a stochastic process hypothesized to occur in a longitudinal data set, testing for other processes is necessary, because incorrect models often fit other processes well enough to be deceiving; (b) when measurement error correlations are flagged to be relatively high in panel data, the fit and propriety of an MA or ARMA model should be considered and compared to the fit and propriety of other models; (c) when an MA model is fit to AR data, measurement error correlations may nonetheless be deceptively high, though fortunately MA model fit indexes are almost always lower than those for an AR model; and (d) the assumption that longitudinal panel data always contain measurement error correlations is patently false. In summary, whenever evaluating longitudinal panel data, the fit, propriety, and parsimony of all 5 models should be considered jointly and compared before a particular model is endorsed as most suitable. 相似文献
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付敏江 《陕西教育学院学报》2005,21(4):73-75
从测量方法与测量误差、测量仪器和条件的选择与测量误差以及数据处理三个方面，阐述了如何将误差分析贯穿于普通物理实验教学，以提高学生综合实验能力． 相似文献
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Christian Geiser Michael Eid Stephen G. West Tanja Lischetzke Fridtjof W. Nussbeck 《Structural equation modeling》2013,20(3):409-436
It is well known that measurement error in observable variables induces bias in estimates in standard regression analysis and that structural equation models are a typical solution to this problem. Often, multiple indicator equations are subsumed as part of the structural equation model, allowing for consistent estimation of the relevant regression parameters. In many instances, however, embedding the measurement model into structural equation models is not possible because the model would not be identified. To correct for measurement error one has no other recourse than to provide the exact values of the variances of the measurement error terms of the model, although in practice such variances cannot be ascertained exactly, but only estimated from an independent study. The usual approach so far has been to treat the estimated values of error variances as if they were known exact population values in the subsequent structural equation modeling (SEM) analysis. In this article we show that fixing measurement error variance estimates as if they were true values can make the reported standard errors of the structural parameters of the model smaller than they should be. Inferences about the parameters of interest will be incorrect if the estimated nature of the variances is not taken into account. For general SEM, we derive an explicit expression that provides the terms to be added to the standard errors provided by the standard SEM software that treats the estimated variances as exact population values. Interestingly, we find there is a differential impact of the corrections to be added to the standard errors depending on which parameter of the model is estimated. The theoretical results are illustrated with simulations and also with empirical data on a typical SEM model. 相似文献
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Equivalent circuit model-based state-of-charge (SOC) estimation has been widely studied for power lithium-ion batteries. An appropriate relaxation period to measure the open-circuit voltage (OCV) should be investigated to both ensure good SOC estimation accuracy and improve OCV test efficiency. Based on a battery circuit model, an SOC estimator in the combination of recursive least squares (RLS) and the extended Kalman filter is used to mitigate the error voltage between the measurement and real values of the battery OCV. To reduce the iterative computation complexity, a two-stage RLS approach is developed to identify the model parameters, the battery circuit of which is divided into two simple circuits. Then, the measurement values of the OCV at varying relaxation periods and three temperatures are sampled to establish the relationships between SOC and OCV for the developed SOC estimator. Lastly, dynamic stress test and federal test procedure drive cycles are used to validate the model-based SOC estimation method. Results show that the relationships between SOC and OCV at a short relaxation time, such as 5 min, can also drive the SOC estimator to produce a good performance. 相似文献
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This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality assumption and using data transformation on repeated measures. Based on unconditional GMM with two latent trajectories, data were generated under different sample sizes (300, 800, and 1500), skewness (0.7, 1.2, and 1.6) and kurtosis (2 and 4) of outcomes, numbers of time points (4 and 8), and class proportions (0.5:0.5 and 0.25:0.75). Of the four distributions, it was found that skew-t GMM had the highest accuracy in terms of parameter estimation. In GMM based on data transformations, the adjusted logarithmic method was more effective in obtaining unbiased parameter estimates than the use of van der Waerden quantile normal scores. Even though adjusted logarithmic transformation in nonnormal GMM reduced computation time, skew-t GMM produced much more accurate estimation and was more robust over a range of simulation conditions. This study is significant in that it considers different levels of kurtosis and class proportions, which has not been investigated in depth in previous studies. The present study is also meaningful in that investigated the applicability of data transformation to nonnormal GMM. 相似文献
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Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal conditions using four latent trait estimation procedures and also evaluated whether the test composition, in terms of item difficulty level, reduces estimation error. Most importantly, both true and estimated item parameters were examined to disentangle the effects of latent trait estimation error from item parameter estimation error. Results revealed that non-normal latent trait distributions produced a considerably larger degree of latent trait estimation error than normal data. Estimated item parameters tended to have comparable precision to true item parameters, thus suggesting that increased latent trait estimation error results from latent trait estimation rather than item parameter estimation. 相似文献