Simulation Studies on Bootstrap Empirical Likelihood Tests

Namba, Akio

doi:10.1081/sac-120028436

Cited by 7 publications

(3 citation statements)

References 16 publications

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“…Second, Monte Carlo simulations with bootstrap sampling of the isotopomer abundances provided an effective method for exploring the flux space that was consistent with the observed redistribution of label. Stochastic sampling of the starting fluxes is routine in the modeling process (Schwender et al, 2006), and combining this with statistical sampling of the data points improves the fitting procedure (Kelly et al, 1990;Namba, 2004). Surprisingly, the availability of a subroutine to exploit this method in the commonly used 13C-FLUX software appears to have been overlooked.…”

Section: Discussionmentioning

confidence: 99%

Subcellular Flux Analysis of Central Metabolism in a Heterotrophic Arabidopsis Cell Suspension Using Steady-State Stable Isotope Labeling

et al. 2009

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The presence of cytosolic and plastidic pathways of carbohydrate oxidation is a characteristic feature of plant cell metabolism. Ideally, steady-state metabolic flux analysis, an emerging tool for creating flux maps of heterotrophic plant metabolism, would capture this feature of the metabolic phenotype, but the extent to which this can be achieved is uncertain. To address this question, fluxes through the pathways of central metabolism in a heterotrophic Arabidopsis (Arabidopsis thaliana) cell suspension culture were deduced from the redistribution of label in steady-state 13 C-labeling experiments using [1-13 C]-, [2-13 C]-, and [U- 13C 6 ]glucose. Focusing on the pentose phosphate pathway (PPP), multiple data sets were fitted simultaneously to models in which the subcellular compartmentation of the PPP was altered. The observed redistribution of the label could be explained by any one of three models of the subcellular compartmentation of the oxidative PPP, but other biochemical evidence favored the model in which the oxidative steps of the PPP were duplicated in the cytosol and plastids, with flux through these reactions occurring largely in the cytosol. The analysis emphasizes the inherent difficulty of analyzing the PPP without predefining the extent of its compartmentation and the importance of obtaining high-quality data that report directly on specific subcellular processes. The Arabidopsis flux map also shows that the potential ATP yield of respiration in heterotrophic plant cells can greatly exceed the direct metabolic requirements for biosynthesis, highlighting the need for caution when predicting flux through metabolic networks using assumptions based on the energetics of resource utilization.Extensive subcellular compartmentation, with unique locations for many steps and pathways, as well as the duplication of other steps and pathways in different compartments, adds greatly to the structural complexity of the plant metabolic network (Lunn, 2007;. The need to consider discrete pools of metabolites in specific compartments, and the transporters that link them, complicates the quest for a detailed, predictive understanding of the regulation of plant metabolism; as a result, it remains difficult to manipulate flows of material through the central metabolic network in a predictable way (Carrari et al., 2003;Sweetlove et al., 2008).The emergence of steady-state metabolic flux analysis (MFA) as a practicable systems biology tool for generating flux maps of the central metabolic pathways in plants offers new opportunities for analyzing plant metabolic phenotypes (Ratcliffe and ShacharHill, 2006;Libourel and Shachar-Hill, 2008;Schwender, 2008;Kruger and Ratcliffe, 2009). In this approach, substrates labeled with stable isotopes are introduced into the network, and fluxes are determined by measuring the labeling of the system after it has reached an isotopic and metabolic steady state. Subcellular compartmentation of steps and pathways can be incorporated into the model that describes the redistribution of t...

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Section: Discussionmentioning

confidence: 99%

Subcellular Flux Analysis of Central Metabolism in a Heterotrophic Arabidopsis Cell Suspension Using Steady-State Stable Isotope Labeling

et al. 2009

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“…The critical value for the profile EL ratio statistic, therefore, cannot be calculated easily using the derived distribution, necessitating the search for alternate methods. Our second approach is to employ the bootstrap to obtain the critical value (Namba, 2004). We compare the performances of the profile EL and NA based approaches through Monte Carlo simulation.…”

Section: Introductionmentioning

confidence: 99%

Censored median regression and profile empirical likelihood

Subramanian

2007

Statistical Methodology

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We implement profile empirical likelihood based inference for censored median regression models. Inference for any specified sub-vector is carried out by profiling out the nuisance parameters from the "plug-in" empirical likelihood ratio function proposed by Qin and Tsao. To obtain the critical value of the profile empirical likelihood ratio statistic, we first investigate its asymptotic distribution. The limiting distribution is a sum of weighted chi square distributions. Unlike for the full empirical likelihood, however, the derived asymptotic distribution has intractable covariance structure. Therefore, we employ the bootstrap to obtain the critical value, and compare the resulting confidence intervals with the ones obtained through Basawa and Koul's minimum dispersion statistic. Furthermore, we obtain confidence intervals for the age and treatment effects in a lung cancer data set.

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“…Deriving the Bartlett correction can be challenging and therefore should be estimated via bootstrap [21], and with an increased computational cost. On the same spirit, [17,[22][23][24][25] proposed bootstrap calibration 3 of the EL test statistic directly. In contrast to EL, the EEL, does not admit Bartlett correction [26] and an adjustment was suggested by [27].…”

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confidence: 99%

Hypothesis testing for two population means: parametric or non-parametric test?

Tsagris

Alenazi

Verrou

et al. 2019

Journal of Statistical Computation and Simulation

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The parametric Welch t-test and the non-parametric Wilcoxon-Mann-Whitney test are the most commonly used two independent sample means tests. More recent testing approaches include the nonparametric, empirical likelihood and exponential empirical likelihood. However, the applicability of these non-parametric likelihood testing procedures is limited partially because of their tendency to inflate the type I error in small sized samples. In order to circumvent the type I error problem, we propose simple calibrations using the t distribution and bootstrapping. The two non-parametric likelihood testing procedures, with and without those calibrations, are then compared against the Wilcoxon-Mann-Whitney test and the Welch t-test. The comparisons are implemented via extensive Monte Carlo simulations on the grounds of type I error and power in small/medium sized samples generated from various nonnormal populations. The simulation studies clearly demonstrate that a) the t calibration improves the type I error of the empirical likelihood, b) bootstrap calibration improves the type I error of both nonparametric likelihoods, c) the Welch t-test with or without bootstrap calibration attains the type I error and produces similar levels of power with the former testing procedures, and d) the Wilcoxon-Mann-Whitney test produces inflated type I error while the computation of an exact p-value is not feasible in the presence of ties with discrete data. Further, an application to real gene expression data illustrates the computational high cost and thus the impracticality of the non parametric likelihoods. Overall, the Welch t-test, which is highly computationally efficient and readily interpretable, is shown to be the best method when testing equality of two population means. keywords: Sections; Hypothesis testing; Welch t-test; empirical likelihood; bootstrap amscode: 62G10; 62F40 1 arXiv:1812.11361v2 [stat.ME] 4 Oct 2019 I error, but the simulation study was rather small and narrow. Deriving the Bartlett correction can be challenging and therefore should be estimated via bootstrap [21], and with an increased computational cost. On the same spirit, [17,[22][23][24][25] proposed bootstrap calibration 3 of the EL test statistic directly. In contrast to EL, the EEL, does not admit Bartlett correction [26] and an adjustment was suggested by [27]. This should not be considered as a disadvantage, according to [28], as the Bartlett correction is sometimes ineffective, while EEL shares the same higher order asymptotic properties of the EL [28] as established in [29]. Finally, the non-parametric WMW test is based on ranks and hence unable to capture the differences in the means. The statistic of the WMW without ties is asymptotically normally distributed and although exact p-value computation is possible it becomes difficult as the number of combinations increase. In the presence of ties in small sample sizes, asymptotic normality does not hold and exact p-value computation is not feasible.The parametric Welch t-test is one of the oldest and...

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Simulation Studies on Bootstrap Empirical Likelihood Tests

Abstract: In this paper we consider to test the hypothesis using the empirical likelihood. To calculate the critical value of the test, two bootstrap methods are applied. Our simulation results indicate that the bootstrap methods improve the small sample property of the test.

Cited by 7 publications

References 16 publications

Subcellular Flux Analysis of Central Metabolism in a Heterotrophic Arabidopsis Cell Suspension Using Steady-State Stable Isotope Labeling

Subcellular Flux Analysis of Central Metabolism in a Heterotrophic Arabidopsis Cell Suspension Using Steady-State Stable Isotope Labeling

Censored median regression and profile empirical likelihood

Hypothesis testing for two population means: parametric or non-parametric test?

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