A revised simplex algorithm for the absolute deviation curve fitting problem

Ronald, Dean; Frome, E. L.; Kung, David S.

doi:10.1080/03610917908812113

Cited by 115 publications

(53 citation statements)

References 11 publications

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“…In general, LAV regression requires three ,Bs represent the log of the SIs for the special computational resources to calculate three concentrations of BeSO4 on harvest parameter estimates (8). In this situation, day 5 and the next three Ps are the corre-however, it is only necessary to find the sponding estimates on day 7.…”

Section: Rerssion Model For the Belpt Datamentioning

confidence: 99%

Statistical Methods for the Blood Beryllium Lymphocyte Proliferation Test

Frome¹,

Smith²,

Littlefield³

et al. 1996

Environmental Health Perspectives

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The blood beryllium lymphocyte proliferation test (BeLPT) is a modification of the standard lymphocyte proliferation test that is used to identify persons who may have chronic beryllium disease. A major problem in the interpretation of BeLPT test results is outlying data values among the replicate well counts (=7%). A log-linear regression model is used to describe the expected well counts for each set of Be exposure conditions, and the variance of the well counts is proportional to the square of the expected count. Two outlier-resistant regression methods are used to estimate stimulation indices (Sls) and the coefficient of variation. The first approach uses least absolute values (LAV) on the log of the well counts as a method for estimation; the second approach uses a resistant regression version of maximum quasi-likelihood estimation. A major advantage of these resistant methods is that they make it unnecessary to identify and delete outliers. These two new methods for the statistical analysis of the BeLPT data and the current outlier rejection method are applied to 173 BeLPT assays. We strongly recommend the LAV method for routine analysis of the BeLPT. Outliers are important when trying to identify individuals with beryllium hypersensitivity, since these individuals typically have large positive SI values. A new method for identifying large Sls using combined data from the nonexposed group and the beryllium workers is proposed. The log(SIl)s are described with a Gaussian distribution with location and scale parameters estimated using resistant methods. This approach is applied to the test data and results are compared with those obtained from the current method. EnvironHealth Perspect 104(Suppl 5): 957-968 (1996)

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Section: Rerssion Model For the Belpt Datamentioning

confidence: 99%

Statistical Methods for the Blood Beryllium Lymphocyte Proliferation Test

Frome¹,

Smith²,

Littlefield³

et al. 1996

Environmental Health Perspectives

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“…Adapting the estimation strategies of Armstrong, Frome and Kung (1979), Barrodale and Roberts (1973), Buchinsky (1994), Chamberlain (1994), and Wagner (1959) the problem of minimization of the sum of absolute deviations of sample wages from an arbitrarily chosen quantile wage can, in the simplest case, be expressed as: The standard errors of the estimated quantile regression coefficients are typically computed by the method of Koenker and Bassett (1982). These standard errors, however, are downward biased because they do not take into account the heteroscedasticity of the disturbance terms.…”

Section: Appendix: Quantile Wage Regression and Bootstrap Standard Ermentioning

confidence: 99%

Labor Unions and the Distribution of Wages and Employment in South Africa

Schultz¹,

Mwabu²

1998

Industrial and Labor Relations Review

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“…12 In this study, the minimisation problem is solved by the linear programming techniques suggested by Amstrong et al, (1979). 13 Although the literature is not definite as to the dbestT path to follow, this does not pose a serious problem.…”

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confidence: 99%

Capital structure in South Korea: a quantile regression approach

Fattouh

Scaramozzino

Harris

2005

Journal of Development Economics

119

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Knowledge of how South Korean firms choose their capital structures has particular value due to the country's specific corporate structure and the role of leverage in the evolution of its financial crisis of 1997 and recovery. Using a large panel for the years 1992-2001, we investigate the evolution and determinants of Korean firms' capital structure and focus on differences between firms in different quantiles of the debt-capital distribution. Conditional quantile regressions show that while variables associated with standard models of asymmetric information costs are significant throughout the distribution, there are considerable differences, including differences in sign, in their impact on firms with different degrees of leverage. Those observed nonlinearities in the determinants of capital structure are consistent with a model of capital structure that includes both costs resulting from asymmetric information and an upper bound on the debt-capital ratio. D

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A revised simplex algorithm for the absolute deviation curve fitting problem

Cited by 115 publications

References 11 publications

Statistical Methods for the Blood Beryllium Lymphocyte Proliferation Test

Statistical Methods for the Blood Beryllium Lymphocyte Proliferation Test

Labor Unions and the Distribution of Wages and Employment in South Africa

Capital structure in South Korea: a quantile regression approach

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