Kosei Iwase

Trihalomethane formation potential prediction using some chemical functional groups and bulk parameters

Abstract This study was conducted to determine the influence of some chemical functional groups (COOH, phenolic-OH and organic nitrogen) and bulk parameters (UV 260 and DOC) on the trihalomethane formation potential (THMFP) of various treated industrial wastewaters. The samples were analyzed for UV 260, DOC, and THMFP. They were further fractionated into hydrophobic (humic) and hydrophilic (nonhumic) fractions using the XAD-8 resin, then bulk and specific chemical functional groups were determined on both fractions. Regression analyses were carried out among the parameters analyzed with THMFP as the dependent variable. The hydrophilic fractions contained higher DOC and had larger contribution to the bulk THMFP compared to the hydrophobic fractions. Simple regression analysis showed that although UV 260 and DOC correlated better with THMFP, the correlation values obtained were not statistically significant. Correlations using bulk parameters as well as chemical functional groups taken one at a time could not predict THMFP. The parameters that influenced the formation of THMs based on a stepwise and multiple regression analyses were UV 260, organic nitrogen, and phenolic-OH in the nonhumic fractions (hydrophilic) and UV 260 and organic nitrogen in the humic fractions (hydrophobic). The estimated THMFP obtained from the equation derived from the statistical analyses correlated significantly with the observed values at 99% level of confidence.

Umvu estimators of the mode and limits of an interval for the inverse gaussian distribution

For a random variable obeying the inverse Gaussian distribu-tion and its reciprocal, the uniformly minimum variance unbiased (UMVU) estimators of each mode are obtained. The UMVU estimators of the left and right limits of a certain interval which contains an inverse Gaussian variate with an arbitrary given probability are also proposed.

Estimation for 3-parameter lognormal distribution with unknown shifted origin

A new reparameterization of a 3-parameter lognormal distribution with unknown shifted origin is presented by using a dimensionless parameter. We avoid, in this article, the application of logarithmic and exponential transformations to a value which has a physical dimension. The distribution function contains two dimensional parameters and one dimensionless parameter. Modified moment estimators and maximum likelihood estimators are presented. The presented modified moment estimators and maximum likelihood estimators are confronted with some actual data.

On umvu estimators for the multivariate lognormal distribution and their variances

Uniformly minimum variance unbiased estimators of several parameters of the multivariate lognormal distribution are expressed by using the hypergeometric functions of matrix argument. And the variances are given in special cases.

Incomplete sufficient unbiased estimators in the problem of the nile

A family of incomplete sufficient unbiased esti¬mators is constructed for an arbitrary power of the parameter in the problem of the Nile. The variance is derived in a closed form and compared numerically with the mean square error of the maximum likelihood es t ima tor

Estimation for a scale parameter with known coefficient of variation

A loss function proposed by Wasan (1970) is well-fitted for a measure of inaccuracy for an estimator of a scale parameter of a distribution defined onR+=(0, ∞). We refer to this loss function as the K-loss function. A relationship between the K-loss and squared error loss functions is discussed. And an optimal estimator for a scale parameter with known coefficient of variation under the K-loss function is presented.